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Books and Theses
- 2014
[b1]Adrian Weller:
Methods for Inference in Graphical Models. Columbia University, USA, 2014
Journal Articles
- 2024
- [j12]Alistair Knott
, Dino Pedreschi, Toshiya Jitsuzumi, Susan Leavy, David M. Eyers, Tapabrata Chakraborti, Andrew Trotman, Sundar Sundareswaran, Ricardo Baeza-Yates, Przemyslaw Biecek, Adrian Weller, Paul D. Teal, Subhadip Basu, Mehmet Haklidir, Virginia Morini, Stuart Russell, Yoshua Bengio:
AI content detection in the emerging information ecosystem: new obligations for media and tech companies. Ethics Inf. Technol. 26(4): 63 (2024) - [j11]Alistair Knott, Dino Pedreschi, Toshiya Jitsuzumi, Susan Leavy, David M. Eyers, Tapabrata Chakraborti, Andrew Trotman, Sundar Sundareswaran, Ricardo Baeza-Yates, Przemyslaw Biecek, Adrian Weller, Paul D. Teal, Subhadip Basu, Mehmet Haklidir, Virginia Morini, Stuart Russell, Yoshua Bengio:
Correction: AI content detection in the emerging information ecosystem: new obligations for media and tech companies. Ethics Inf. Technol. 26(4): 71 (2024) - 2023
- [j10]Weiyang Liu, Yandong Wen, Bhiksha Raj, Rita Singh, Adrian Weller:
SphereFace Revived: Unifying Hyperspherical Face Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 2458-2474 (2023) - [j9]Christian Knoll, Adrian Weller, Franz Pernkopf:
Self-Guided Belief Propagation - A Homotopy Continuation Method. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 5139-5157 (2023) - [j8]Valerie Chen, Umang Bhatt, Hoda Heidari, Adrian Weller, Ameet Talwalkar:
Perspectives on incorporating expert feedback into model updates. Patterns 4(7): 100780 (2023) - [j7]Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, Weiyang Liu:
Continual Learning by Modeling Intra-Class Variation. Trans. Mach. Learn. Res. 2023 (2023) - 2022
- [j6]Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuansheng Zheng, Jianming Wang, Zhen Li, Carola Schönlieb, Tian Xia:
Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence. Nat. Mach. Intell. 4(4): 413 (2022) - [j5]John Zerilli, Umang Bhatt, Adrian Weller:
How transparency modulates trust in artificial intelligence. Patterns 3(4): 100455 (2022) - 2021
- [j4]Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuansheng Zheng, Jianming Wang, Zhen Li, Carola Schönlieb, Tian Xia:
Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence. Nat. Mach. Intell. 3(12): 1081-1089 (2021) - 2020
- [j3]Siddique Latif, Muhammad Usman, Sanaullah Manzoor, Waleed Iqbal, Junaid Qadir, Gareth Tyson, Ignacio Castro, Adeel Razi, Maged N. Kamel Boulos, Adrian Weller, Jon Crowcroft:
Leveraging Data Science to Combat COVID-19: A Comprehensive Review. IEEE Trans. Artif. Intell. 1(1): 85-103 (2020) - 2019
- [j2]Ofer Meshi, Ben London, Adrian Weller, David A. Sontag:
Train and Test Tightness of LP Relaxations in Structured Prediction. J. Mach. Learn. Res. 20: 13:1-13:34 (2019) - [j1]Stephen Cave, Rune Nyrup, Karina Vold, Adrian Weller:
Motivations and Risks of Machine Ethics. Proc. IEEE 107(3): 562-574 (2019)
Conference and Workshop Papers
- 2024
- [c119]Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller:
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. AISTATS 2024: 2278-2286 - [c118]Weiyang Liu, Zeju Qiu, Yao Feng, Yuliang Xiu, Yuxuan Xue, Longhui Yu, Haiwen Feng, Zhen Liu, Juyeon Heo, Songyou Peng, Yandong Wen, Michael J. Black, Adrian Weller, Bernhard Schölkopf:
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization. ICLR 2024 - [c117]Isaac Reid, Eli Berger, Krzysztof Marcin Choromanski, Adrian Weller:
Repelling Random Walks. ICLR 2024 - [c116]Isaac Reid, Krzysztof Marcin Choromanski, Eli Berger, Adrian Weller:
General Graph Random Features. ICLR 2024 - [c115]Ali Shahin Shamsabadi, Gefei Tan, Tudor Cebere, Aurélien Bellet, Hamed Haddadi, Nicolas Papernot, Xiao Wang, Adrian Weller:
Confidential-DPproof: Confidential Proof of Differentially Private Training. ICLR 2024 - [c114]Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T. Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu:
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models. ICLR 2024 - 2023
- [c113]Javier Abad Martinez, Umang Bhatt, Adrian Weller, Giovanni Cherubin:
Approximating Full Conformal Prediction at Scale via Influence Functions. AAAI 2023: 6631-6639 - [c112]Sunghwan Joo, Seokhyeon Jeong, Juyeon Heo, Adrian Weller, Taesup Moon:
Towards More Robust Interpretation via Local Gradient Alignment. AAAI 2023: 8168-8176 - [c111]Valerii Likhosherstov, Krzysztof Choromanski, Adrian Weller:
On the Expressive Flexibility of Self-Attention Matrices. AAAI 2023: 8773-8781 - [c110]Vedant Nanda, Ayan Majumdar, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Bradley C. Love, Adrian Weller:
Do Invariances in Deep Neural Networks Align with Human Perception? AAAI 2023: 9277-9285 - [c109]Mateo Espinosa Zarlenga, Pietro Barbiero, Zohreh Shams, Dmitry Kazhdan, Umang Bhatt, Adrian Weller, Mateja Jamnik:
Towards Robust Metrics for Concept Representation Evaluation. AAAI 2023: 11791-11799 - [c108]Katherine Maeve Collins, Matthew Barker, Mateo Espinosa Zarlenga, Naveen Raman, Umang Bhatt, Mateja Jamnik, Ilia Sucholutsky, Adrian Weller, Krishnamurthy Dvijotham:
Human Uncertainty in Concept-Based AI Systems. AIES 2023: 869-889 - [c107]Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf:
Iterative Teaching by Data Hallucination. AISTATS 2023: 9892-9913 - [c106]Carolyn Ashurst, Adrian Weller:
Fairness Without Demographic Data: A Survey of Approaches. EAAMO 2023: 14:1-14:12 - [c105]Matthew Barker, Emma Kallina, Dhananjay Ashok, Katherine M. Collins, Ashley Casovan, Adrian Weller, Ameet Talwalkar, Valerie Chen, Umang Bhatt:
FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines. EAAMO 2023: 19:1-19:15 - [c104]Harry Camilleri, Carolyn Ashurst, Nithya Jaisankar, Adrian Weller, Miri Zilka:
Media Coverage of Predictive Policing: Bias, Police Engagement, and the Future of Transparency. EAAMO 2023: 28:1-28:19 - [c103]Alan Chan, Rebecca Salganik, Alva Markelius, Chris Pang, Nitarshan Rajkumar, Dmitrii Krasheninnikov, Lauro Langosco, Zhonghao He, Yawen Duan, Micah Carroll, Michelle Lin, Alex Mayhew, Katherine M. Collins, Maryam Molamohammadi, John Burden, Wanru Zhao, Shalaleh Rismani, Konstantinos Voudouris, Umang Bhatt, Adrian Weller, David Krueger, Tegan Maharaj:
Harms from Increasingly Agentic Algorithmic Systems. FAccT 2023: 651-666 - [c102]Miri Zilka, Riccardo Fogliato, Jiri Hron, Bradley Butcher, Carolyn Ashurst, Adrian Weller:
The Progression of Disparities within the Criminal Justice System: Differential Enforcement and Risk Assessment Instruments. FAccT 2023: 1553-1569 - [c101]Yandong Wen, Weiyang Liu, Yao Feng, Bhiksha Raj, Rita Singh, Adrian Weller, Michael J. Black, Bernhard Schölkopf:
Pairwise Similarity Learning is SimPLE. ICCV 2023: 5285-5295 - [c100]Weiyang Liu, Longhui Yu, Adrian Weller, Bernhard Schölkopf:
Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap. ICLR 2023 - [c99]Vivek Palaniappan, Matthew Ashman, Katherine M. Collins, Juyeon Heo, Adrian Weller, Umang Bhatt:
GeValDi: Generative Validation of Discriminative Models. Tiny Papers @ ICLR 2023 - [c98]Ali Shahin Shamsabadi, Sierra Calanda Wyllie, Nicholas Franzese, Natalie Dullerud, Sébastien Gambs, Nicolas Papernot, Xiao Wang, Adrian Weller:
Confidential-PROFITT: Confidential PROof of FaIr Training of Trees. ICLR 2023 - [c97]Matthew Wicker, Juyeon Heo, Luca Costabello, Adrian Weller:
Robust Explanation Constraints for Neural Networks. ICLR 2023 - [c96]Yanzhi Chen, Michael U. Gutmann, Adrian Weller:
Is Learning Summary Statistics Necessary for Likelihood-free Inference? ICML 2023: 4529-4544 - [c95]Krzysztof Marcin Choromanski, Arijit Sehanobish, Han Lin, Yunfan Zhao, Eli Berger, Tetiana Parshakova, Alvin Pan, David Watkins, Tianyi Zhang, Valerii Likhosherstov, Somnath Basu Roy Chowdhury, Kumar Avinava Dubey, Deepali Jain, Tamás Sarlós, Snigdha Chaturvedi, Adrian Weller:
Efficient Graph Field Integrators Meet Point Clouds. ICML 2023: 5978-6004 - [c94]Isaac Reid, Krzysztof Marcin Choromanski, Valerii Likhosherstov, Adrian Weller:
Simplex Random Features. ICML 2023: 28864-28888 - [c93]Juyeon Heo, Pingfan Song, Weiyang Liu, Adrian Weller:
Physics-Based Decoding Improves Magnetic Resonance Fingerprinting. MICCAI (2) 2023: 446-456 - [c92]Juyeon Heo, Vihari Piratla, Matthew Wicker, Adrian Weller:
Use perturbations when learning from explanations. NeurIPS 2023 - [c91]Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller:
Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel. NeurIPS 2023 - [c90]Vedant Nanda, Till Speicher, John P. Dickerson, Krishna P. Gummadi, Soheil Feizi, Adrian Weller:
Diffused Redundancy in Pre-trained Representations. NeurIPS 2023 - [c89]Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng, Zhen Liu, Dan Zhang, Adrian Weller, Bernhard Schölkopf:
Controlling Text-to-Image Diffusion by Orthogonal Finetuning. NeurIPS 2023 - [c88]Isaac Reid, Adrian Weller, Krzysztof Marcin Choromanski:
Quasi-Monte Carlo Graph Random Features. NeurIPS 2023 - [c87]Matthew Wicker, Vihari Piratla, Adrian Weller:
Certification of Distributional Individual Fairness. NeurIPS 2023 - [c86]Mateo Espinosa Zarlenga, Katie Collins, Krishnamurthy Dvijotham, Adrian Weller, Zohreh Shams, Mateja Jamnik:
Learning to Receive Help: Intervention-Aware Concept Embedding Models. NeurIPS 2023 - [c85]Katherine M. Collins, Umang Bhatt, Weiyang Liu, Vihari Piratla, Ilia Sucholutsky, Bradley C. Love, Adrian Weller:
Human-in-the-Loop Mixup. UAI 2023: 454-464 - [c84]Ali Shahin Shamsabadi, Jamie Hayes, Borja Balle, Adrian Weller:
Mnemonist: Locating Model Parameters that Memorize Training Examples. UAI 2023: 1879-1888 - [c83]Ilia Sucholutsky, Ruairidh M. Battleday, Katherine M. Collins, Raja Marjieh, Joshua C. Peterson, Pulkit Singh, Umang Bhatt, Nori Jacoby, Adrian Weller, Thomas L. Griffiths:
On the informativeness of supervision signals. UAI 2023: 2036-2046 - 2022
- [c82]Dan Ley, Umang Bhatt, Adrian Weller:
Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates. AAAI 2022: 7390-7398 - [c81]Julius von Kügelgen, Amir-Hossein Karimi, Umang Bhatt, Isabel Valera, Adrian Weller, Bernhard Schölkopf:
On the Fairness of Causal Algorithmic Recourse. AAAI 2022: 9584-9594 - [c80]Ahmad Khajehnejad, Moein Khajehnejad, Mahmoudreza Babaei, Krishna P. Gummadi, Adrian Weller, Baharan Mirzasoleiman:
CrossWalk: Fairness-Enhanced Node Representation Learning. AAAI 2022: 11963-11970 - [c79]Bradley Butcher, Christopher Robinson, Miri Zilka, Riccardo Fogliato, Carolyn Ashurst, Adrian Weller:
Racial Disparities in the Enforcement of Marijuana Violations in the US. AIES 2022: 130-143 - [c78]Miri Zilka, Holli Sargeant, Adrian Weller:
Transparency, Governance and Regulation of Algorithmic Tools Deployed in the Criminal Justice System: a UK Case Study. AIES 2022: 880-889 - [c77]Luca Viano, Yu-Ting Huang, Parameswaran Kamalaruban, Craig Innes, Subramanian Ramamoorthy, Adrian Weller:
Robust Learning from Observation with Model Misspecification. AAMAS 2022: 1337-1345 - [c76]Hanlin Zhang, Yi-Fan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric P. Xing:
Towards Principled Disentanglement for Domain Generalization. CVPR 2022: 8014-8024 - [c75]Nina Grgic-Hlaca, Gabriel Lima, Adrian Weller, Elissa M. Redmiles:
Dimensions of Diversity in Human Perceptions of Algorithmic Fairness. EAAMO 2022: 21:1-21:12 - [c74]Weiyang Liu, Zhen Liu, Liam Paull, Adrian Weller, Bernhard Schölkopf:
Structural Causal 3D Reconstruction. ECCV (1) 2022: 140-159 - [c73]Isabel Chien, Nina Deliu, Richard E. Turner, Adrian Weller, Sofia S. Villar, Niki Kilbertus:
Multi-disciplinary fairness considerations in machine learning for clinical trials. FAccT 2022: 906-924 - [c72]Katherine M. Collins, Umang Bhatt, Adrian Weller:
Eliciting and Learning with Soft Labels from Every Annotator. HCOMP 2022: 40-52 - [c71]Krzysztof Marcin Choromanski, Han Lin, Haoxian Chen, Arijit Sehanobish, Yuanzhe Ma, Deepali Jain, Jake Varley, Andy Zeng, Michael S. Ryoo, Valerii Likhosherstov, Dmitry Kalashnikov, Vikas Sindhwani, Adrian Weller:
Hybrid Random Features. ICLR 2022 - [c70]Yandong Wen, Weiyang Liu, Adrian Weller, Bhiksha Raj, Rita Singh:
SphereFace2: Binary Classification is All You Need for Deep Face Recognition. ICLR 2022 - [c69]Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamás Sarlós, Adrian Weller, Thomas Weingarten:
From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers. ICML 2022: 3962-3983 - [c68]Vedant Nanda, Till Speicher, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Adrian Weller:
Measuring Representational Robustness of Neural Networks Through Shared Invariances. ICML 2022: 16368-16382 - [c67]Varun Babbar, Umang Bhatt, Adrian Weller:
On the Utility of Prediction Sets in Human-AI Teams. IJCAI 2022: 2457-2463 - [c66]Yanzhi Chen, Weihao Sun, Yingzhen Li, Adrian Weller:
Scalable Infomin Learning. NeurIPS 2022 - [c65]Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller:
Chefs' Random Tables: Non-Trigonometric Random Features. NeurIPS 2022 - [c64]Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Zohreh Shams, Frédéric Precioso, Stefano Melacci, Adrian Weller, Pietro Lió, Mateja Jamnik:
Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off. NeurIPS 2022 - [c63]Miri Zilka, Bradley Butcher, Adrian Weller:
A Survey and Datasheet Repository of Publicly Available US Criminal Justice Datasets. NeurIPS 2022 - 2021
- [c62]Michiel A. Bakker, Duy Patrick Tu, Krishna P. Gummadi, Alex 'Sandy' Pentland, Kush R. Varshney, Adrian Weller:
Beyond Reasonable Doubt: Improving Fairness in Budget-Constrained Decision Making using Confidence Thresholds. AIES 2021: 346-356 - [c61]Umang Bhatt, Javier Antorán, Yunfeng Zhang, Q. Vera Liao, Prasanna Sattigeri, Riccardo Fogliato, Gabrielle Gauthier Melançon, Ranganath Krishnan, Jason Stanley, Omesh Tickoo, Lama Nachman, Rumi Chunara, Madhulika Srikumar, Adrian Weller, Alice Xiang:
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. AIES 2021: 401-413 - [c60]Joshua Simons, Sophia Adams Bhatti, Adrian Weller:
Machine Learning and the Meaning of Equal Treatment. AIES 2021: 956-966 - [c59]Valerii Likhosherstov, Jared Davis, Krzysztof Choromanski, Adrian Weller:
CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices. AISTATS 2021: 55-63 - [c58]Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller:
Learning with Hyperspherical Uniformity. AISTATS 2021: 1180-1188 - [c57]Umang Bhatt, Adrian Weller, Giovanni Cherubin:
Fast conformal classification using influence functions. COPA 2021: 303-305 - [c56]Weiyang Liu, Rongmei Lin, Zhen Liu, James M. Rehg, Liam Paull, Li Xiong, Le Song, Adrian Weller:
Orthogonal Over-Parameterized Training. CVPR 2021: 7251-7260 - [c55]Oliver Thomas, Miri Zilka, Adrian Weller, Novi Quadrianto:
An Algorithmic Framework for Positive Action. EAAMO 2021: 18:1-18:13 - [c54]Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández-Lobato:
Getting a CLUE: A Method for Explaining Uncertainty Estimates. ICLR 2021 - [c53]Krzysztof Marcin Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamás Sarlós, Peter Hawkins, Jared Quincy Davis, Afroz Mohiuddin, Lukasz Kaiser, David Benjamin Belanger, Lucy J. Colwell, Adrian Weller:
Rethinking Attention with Performers. ICLR 2021 - [c52]Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Quincy Davis, Adrian Weller:
Debiasing a First-order Heuristic for Approximate Bi-level Optimization. ICML 2021: 6621-6630 - [c51]Valerii Likhosherstov, Krzysztof Marcin Choromanski, Jared Quincy Davis, Xingyou Song, Adrian Weller:
Sub-Linear Memory: How to Make Performers SLiM. NeurIPS 2021: 6707-6719 - [c50]Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller:
Iterative Teaching by Label Synthesis. NeurIPS 2021: 21681-21695 - [c49]Luca Viano, Yu-Ting Huang, Parameswaran Kamalaruban, Adrian Weller, Volkan Cevher:
Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch. NeurIPS 2021: 25917-25931 - 2020
- [c48]Michiel A. Bakker, Humberto Riverón Valdés, Duy Patrick Tu, Krishna P. Gummadi, Kush R. Varshney, Adrian Weller, Alex Pentland:
Fair Enough: Improving Fairness in Budget-Constrained Decision Making Using Confidence Thresholds. SafeAI@AAAI 2020: 41-53 - [c47]Botty Dimanov, Umang Bhatt, Mateja Jamnik, Adrian Weller:
You Shouldn't Trust Me: Learning Models Which Conceal Unfairness From Multiple Explanation Methods. SafeAI@AAAI 2020: 63-73 - [c46]Min Kyung Lee, Nina Grgic-Hlaca, Michael Carl Tschantz, Reuben Binns, Adrian Weller, Michelle Carney, Kori Inkpen:
Human-Centered Approaches to Fair and Responsible AI. CHI Extended Abstracts 2020: 1-8 - [c45]Dmitry Kazhdan, Botty Dimanov, Mateja Jamnik, Pietro Liò, Adrian Weller:
Now You See Me (CME): Concept-based Model Extraction. CIKM (Workshops) 2020 - [c44]Botty Dimanov, Umang Bhatt, Mateja Jamnik, Adrian Weller:
You Shouldn't Trust Me: Learning Models Which Conceal Unfairness from Multiple Explanation Methods. ECAI 2020: 2473-2480 - [c43]Umang Bhatt, Alice Xiang, Shubham Sharma, Adrian Weller, Ankur Taly, Yunhan Jia, Joydeep Ghosh, Ruchir Puri, José M. F. Moura, Peter Eckersley:
Explainable machine learning in deployment. FAT* 2020: 648-657 - [c42]Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamás Sarlós, Adrian Weller, Vikas Sindhwani:
Stochastic Flows and Geometric Optimization on the Orthogonal Group. ICML 2020: 1918-1928 - [c41]Umang Bhatt, Adrian Weller, José M. F. Moura:
Evaluating and Aggregating Feature-based Model Explanations. IJCAI 2020: 3016-3022 - [c40]Moein Khajehnejad, Ahmad Asgharian Rezaei, Mahmoudreza Babaei, Jessica Hoffmann, Mahdi Jalili, Adrian Weller:
Adversarial Graph Embeddings for Fair Influence Maximization over Social Networks. IJCAI 2020: 4306-4312 - [c39]Krzysztof Marcin Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani:
Ode to an ODE. NeurIPS 2020 - 2019
- [c38]Tameem Adel, Isabel Valera, Zoubin Ghahramani, Adrian Weller:
One-Network Adversarial Fairness. AAAI 2019: 2412-2420 - [c37]Mark Rowland, Jiri Hron, Yunhao Tang, Krzysztof Choromanski, Tamás Sarlós, Adrian Weller:
Orthogonal Estimation of Wasserstein Distances. AISTATS 2019: 186-195 - [c36]Tameem Adel, Adrian Weller:
TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning. ICML 2019: 71-81 - [c35]Krzysztof Choromanski, Mark Rowland, Wenyu Chen, Adrian Weller:
Unifying Orthogonal Monte Carlo Methods. ICML 2019: 1203-1212 - [c34]Justus Bogner, Adrian Weller, Stefan Wagner, Alfred Zimmermann:
Exploring Maintainability Assurance Research for Service- and Microservice-Based Systems: Directions and Differences. Microservices 2019: 3:1-3:22 - [c33]Yunfei Teng, Wenbo Gao, François Chalus, Anna Choromanska, Donald Goldfarb, Adrian Weller:
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models. NeurIPS 2019: 9821-9831 - [c32]Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva:
The Sensitivity of Counterfactual Fairness to Unmeasured Confounding. UAI 2019: 616-626 - 2018
- [c31]Nina Grgic-Hlaca, Muhammad Bilal Zafar, Krishna P. Gummadi, Adrian Weller:
Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning. AAAI 2018: 51-60 - [c30]Mahmoudreza Babaei, Juhi Kulshrestha, Abhijnan Chakraborty, Fabrício Benevenuto, Krishna P. Gummadi, Adrian Weller:
Purple Feed: Identifying High Consensus News Posts on Social Media. AIES 2018: 10-16 - [c29]Krzysztof Choromanski, Mark Rowland, Tamás Sarlós, Vikas Sindhwani, Richard E. Turner, Adrian Weller:
The Geometry of Random Features. AISTATS 2018: 1-9 - [c28]Sungsoo Ahn, Michael Chertkov, Jinwoo Shin, Adrian Weller:
Gauged Mini-Bucket Elimination for Approximate Inference. AISTATS 2018: 10-19 - [c27]Tameem Adel, Zoubin Ghahramani, Adrian Weller:
Discovering Interpretable Representations for Both Deep Generative and Discriminative Models. ICML 2018: 50-59 - [c26]Sungsoo Ahn, Michael Chertkov, Adrian Weller, Jinwoo Shin:
Bucket Renormalization for Approximate Inference. ICML 2018: 109-118 - [c25]Krzysztof Choromanski, Mark Rowland, Vikas Sindhwani, Richard E. Turner, Adrian Weller:
Structured Evolution with Compact Architectures for Scalable Policy Optimization. ICML 2018: 969-977 - [c24]Niki Kilbertus, Adrià Gascón, Matt J. Kusner, Michael Veale, Krishna P. Gummadi, Adrian Weller:
Blind Justice: Fairness with Encrypted Sensitive Attributes. ICML 2018: 2635-2644 - [c23]Till Speicher, Hoda Heidari, Nina Grgic-Hlaca, Krishna P. Gummadi, Adish Singla, Adrian Weller, Muhammad Bilal Zafar:
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices. KDD 2018: 2239-2248 - [c22]Mark Rowland, Krzysztof Choromanski, François Chalus, Aldo Pacchiano, Tamás Sarlós, Richard E. Turner, Adrian Weller:
Geometrically Coupled Monte Carlo Sampling. NeurIPS 2018: 195-205 - [c21]Nina Grgic-Hlaca, Elissa M. Redmiles, Krishna P. Gummadi, Adrian Weller:
Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction. WWW 2018: 903-912 - 2017
- [c20]Mark Rowland, Aldo Pacchiano, Adrian Weller:
Conditions beyond treewidth for tightness of higher-order LP relaxations. AISTATS 2017: 10-18 - [c19]Matej Balog, Nilesh Tripuraneni, Zoubin Ghahramani, Adrian Weller:
Lost Relatives of the Gumbel Trick. ICML 2017: 371-379 - [c18]Rowan McAllister, Yarin Gal, Alex Kendall, Mark van der Wilk, Amar Shah, Roberto Cipolla, Adrian Weller:
Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning. IJCAI 2017: 4745-4753 - [c17]Mark Rowland, Adrian Weller:
Uprooting and Rerooting Higher-Order Graphical Models. NIPS 2017: 209-218 - [c16]Krzysztof Marcin Choromanski, Mark Rowland, Adrian Weller:
The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings. NIPS 2017: 219-228 - [c15]Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez-Rodriguez, Krishna P. Gummadi, Adrian Weller:
From Parity to Preference-based Notions of Fairness in Classification. NIPS 2017: 229-239 - [c14]Sankalp Bhatnagar, Anna Alexandrova, Shahar Avin, Stephen Cave, Lucy Cheke, Matthew Crosby, Jan Feyereisl, Marta Halina, Bao Sheng Loe, Seán Ó hÉigeartaigh, Fernando Martínez-Plumed, Huw Price, Henry Shevlin, Adrian Weller, Alan F. T. Winfield, José Hernández-Orallo:
Mapping Intelligence: Requirements and Possibilities. PT-AI 2017: 117-135 - 2016
- [c13]Adrian Weller, Justin Domke:
Clamping Improves TRW and Mean Field Approximations. AISTATS 2016: 38-46 - [c12]Adrian Weller, Mark Rowland, David A. Sontag:
Tightness of LP Relaxations for Almost Balanced Models. AISTATS 2016: 47-55 - [c11]Adrian Weller:
Uprooting and Rerooting Graphical Models. ICML 2016: 21-29 - [c10]Ofer Meshi, Mehrdad Mahdavi, Adrian Weller, David A. Sontag:
Train and Test Tightness of LP Relaxations in Structured Prediction. ICML 2016: 1776-1785 - [c9]Adrian Weller:
Characterizing Tightness of LP Relaxations by Forbidding Signed Minors. UAI 2016 - 2015
- [c8]Adrian Weller:
Revisiting the Limits of MAP Inference by MWSS on Perfect Graphs. AISTATS 2015 - [c7]Adrian Weller:
Bethe and Related Pairwise Entropy Approximations. UAI 2015: 942-951 - 2014
- [c6]Adrian Weller, Tony Jebara:
Clamping Variables and Approximate Inference. NIPS 2014: 909-917 - [c5]Adrian Weller, Tony Jebara:
Approximating the Bethe Partition Function. UAI 2014: 858-867 - [c4]Adrian Weller, Kui Tang, Tony Jebara, David A. Sontag:
Understanding the Bethe Approximation: When and How can it go Wrong? UAI 2014: 868-877 - 2013
- [c3]Adrian Weller, Tony Jebara:
Bethe Bounds and Approximating the Global Optimum. AISTATS 2013: 618-631 - [c2]Adrian Weller, Tony Jebara:
On MAP Inference by MWSS on Perfect Graphs. UAI 2013 - 2009
- [c1]Adrian Weller, Daniel P. W. Ellis, Tony Jebara:
Structured Prediction Models for Chord Transcription of Music Audio. ICMLA 2009: 590-595
Parts in Books or Collections
- 2019
- [p1]Adrian Weller:
Transparency: Motivations and Challenges. Explainable AI 2019: 23-40
Informal and Other Publications
- 2024
- [i124]Girish Sastry, Lennart Heim, Haydn Belfield, Markus Anderljung, Miles Brundage, Julian Hazell, Cullen O'Keefe, Gillian K. Hadfield, Richard Ngo, Konstantin Pilz, George Gor, Emma Bluemke, Sarah Shoker, Janet Egan, Robert F. Trager, Shahar Avin, Adrian Weller, Yoshua Bengio, Diane Coyle:
Computing Power and the Governance of Artificial Intelligence. CoRR abs/2402.08797 (2024) - [i123]Isaac Reid, Stratis Markou, Krzysztof Choromanski, Richard E. Turner, Adrian Weller:
Variance-Reducing Couplings for Random Features: Perspectives from Optimal Transport. CoRR abs/2405.16541 (2024) - [i122]Ilia Sucholutsky, Katherine M. Collins, Maya Malaviya, Nori Jacoby, Weiyang Liu, Theodore R. Sumers, Michalis Korakakis, Umang Bhatt, Mark K. Ho, Joshua B. Tenenbaum, Bradley C. Love, Zachary A. Pardos, Adrian Weller, Thomas L. Griffiths:
Representational Alignment Supports Effective Machine Teaching. CoRR abs/2406.04302 (2024) - [i121]Sanyam Kapoor, Nate Gruver, Manley Roberts, Katherine M. Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson:
Large Language Models Must Be Taught to Know What They Don't Know. CoRR abs/2406.08391 (2024) - [i120]Matthew Wicker, Philip Sosnin, Adrianna Janik, Mark N. Müller, Adrian Weller, Calvin Tsay:
Certificates of Differential Privacy and Unlearning for Gradient-Based Training. CoRR abs/2406.13433 (2024) - [i119]Matthew Ashman, Cristiana Diaconu, Adrian Weller, Wessel P. Bruinsma, Richard E. Turner:
Approximately Equivariant Neural Processes. CoRR abs/2406.13488 (2024) - [i118]Matthew Ashman, Cristiana Diaconu, Adrian Weller, Richard E. Turner:
In-Context In-Context Learning with Transformer Neural Processes. CoRR abs/2406.13493 (2024) - [i117]Katherine M. Collins, Najoung Kim, Yonatan Bitton, Verena Rieser, Shayegan Omidshafiei, Yushi Hu, Sherol Chen, Senjuti Dutta, Minsuk Chang, Kimin Lee, Youwei Liang, Georgina Evans, Sahil Singla, Gang Li, Adrian Weller, Junfeng He, Deepak Ramachandran, Krishnamurthy Dj Dvijotham:
Beyond Thumbs Up/Down: Untangling Challenges of Fine-Grained Feedback for Text-to-Image Generation. CoRR abs/2406.16807 (2024) - [i116]Katherine M. Collins, Valerie Chen, Ilia Sucholutsky, Hannah Rose Kirk, Malak Sadek, Holli Sargeant, Ameet Talwalkar, Adrian Weller, Umang Bhatt:
Modulating Language Model Experiences through Frictions. CoRR abs/2407.12804 (2024) - [i115]Cedegao E. Zhang, Katherine M. Collins, Lionel Wong, Adrian Weller, Joshua B. Tenenbaum:
People use fast, goal-directed simulation to reason about novel games. CoRR abs/2407.14095 (2024) - [i114]Katherine M. Collins, Ilia Sucholutsky, Umang Bhatt, Kartik Chandra, Lionel Wong, Mina Lee, Cedegao E. Zhang, Tan Zhi-Xuan, Mark K. Ho, Vikash Mansinghka, Adrian Weller, Joshua B. Tenenbaum, Thomas L. Griffiths:
Building Machines that Learn and Think with People. CoRR abs/2408.03943 (2024) - [i113]Zeju Qiu, Weiyang Liu, Haiwen Feng, Zhen Liu, Tim Z. Xiao, Katherine M. Collins, Joshua B. Tenenbaum, Adrian Weller, Michael J. Black, Bernhard Schölkopf:
Can Large Language Models Understand Symbolic Graphics Programs? CoRR abs/2408.08313 (2024) - [i112]Yanzhi Chen, Zijing Ou, Adrian Weller, Yingzhen Li:
Mutual Information Multinomial Estimation. CoRR abs/2408.09377 (2024) - [i111]Aoting Hu, Yanzhi Chen, Renjie Xie, Adrian Weller:
On the Weaknesses of Backdoor-based Model Watermarking: An Information-theoretic Perspective. CoRR abs/2409.06130 (2024) - 2023
- [i110]Mateo Espinosa Zarlenga, Pietro Barbiero, Zohreh Shams, Dmitry Kazhdan, Umang Bhatt, Adrian Weller, Mateja Jamnik:
Towards Robust Metrics for Concept Representation Evaluation. CoRR abs/2301.10367 (2023) - [i109]Isaac Reid, Krzysztof Choromanski, Valerii Likhosherstov, Adrian Weller:
Simplex Random Features. CoRR abs/2301.13856 (2023) - [i108]Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller:
FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features. CoRR abs/2302.00787 (2023) - [i107]Krzysztof Choromanski, Arijit Sehanobish, Han Lin, Yunfan Zhao, Eli Berger, Tetiana Parshakova, Alvin Pan, David Watkins, Tianyi Zhang, Valerii Likhosherstov, Somnath Basu Roy Chowdhury, Avinava Dubey, Deepali Jain, Tamás Sarlós, Snigdha Chaturvedi, Adrian Weller:
Efficient Graph Field Integrators Meet Point Clouds. CoRR abs/2302.00942 (2023) - [i106]Krzysztof Marcin Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller:
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. CoRR abs/2302.01925 (2023) - [i105]Bradley Butcher, Miri Zilka, Darren Cook, Jiri Hron, Adrian Weller:
Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents. CoRR abs/2302.09324 (2023) - [i104]Alan Chan, Rebecca Salganik, Alva Markelius, Chris Pang, Nitarshan Rajkumar, Dmitrii Krasheninnikov, Lauro Langosco, Zhonghao He, Yawen Duan, Micah Carroll, Michelle Lin, Alex Mayhew, Katherine M. Collins, Maryam Molamohammadi, John Burden, Wanru Zhao, Shalaleh Rismani, Konstantinos Voudouris, Umang Bhatt, Adrian Weller, David Krueger, Tegan Maharaj:
Harms from Increasingly Agentic Algorithmic Systems. CoRR abs/2302.10329 (2023) - [i103]Yanzhi Chen, Weihao Sun, Yingzhen Li, Adrian Weller:
Scalable Infomin Learning. CoRR abs/2302.10701 (2023) - [i102]Juyeon Heo, Vihari Piratla, Matthew Wicker, Adrian Weller:
Robust Learning from Explanations. CoRR abs/2303.06419 (2023) - [i101]Weiyang Liu, Longhui Yu, Adrian Weller, Bernhard Schölkopf:
Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap. CoRR abs/2303.06484 (2023) - [i100]Katherine M. Collins, Matthew Barker, Mateo Espinosa Zarlenga, Naveen Raman, Umang Bhatt, Mateja Jamnik, Ilia Sucholutsky, Adrian Weller, Krishnamurthy Dvijotham:
Human Uncertainty in Concept-Based AI Systems. CoRR abs/2303.12872 (2023) - [i99]Umang Bhatt, Valerie Chen, Katherine M. Collins, Parameswaran Kamalaruban, Emma Kallina, Adrian Weller, Ameet Talwalkar:
Learning Personalized Decision Support Policies. CoRR abs/2304.06701 (2023) - [i98]Miri Zilka, Riccardo Fogliato, Jiri Hron, Bradley Butcher, Carolyn Ashurst, Adrian Weller:
The Progression of Disparities within the Criminal Justice System: Differential Enforcement and Risk Assessment Instruments. CoRR abs/2305.07575 (2023) - [i97]Isaac Reid, Krzysztof Choromanski, Adrian Weller:
Quasi-Monte Carlo Graph Random Features. CoRR abs/2305.12470 (2023) - [i96]Vedant Nanda, Till Speicher, John P. Dickerson, Soheil Feizi, Krishna P. Gummadi, Adrian Weller:
Diffused Redundancy in Pre-trained Representations. CoRR abs/2306.00183 (2023) - [i95]Katherine M. Collins, Albert Q. Jiang, Simon Frieder, Lionel Wong, Miri Zilka, Umang Bhatt, Thomas Lukasiewicz, Yuhuai Wu, Joshua B. Tenenbaum, William Hart, Timothy Gowers, Wenda Li, Adrian Weller, Mateja Jamnik:
Evaluating Language Models for Mathematics through Interactions. CoRR abs/2306.01694 (2023) - [i94]Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng, Zhen Liu, Dan Zhang, Adrian Weller, Bernhard Schölkopf:
Controlling Text-to-Image Diffusion by Orthogonal Finetuning. CoRR abs/2306.07280 (2023) - [i93]Matthew Barker, Katherine M. Collins, Krishnamurthy Dvijotham, Adrian Weller, Umang Bhatt:
Selective Concept Models: Permitting Stakeholder Customisation at Test-Time. CoRR abs/2306.08424 (2023) - [i92]Lance Ying, Katherine M. Collins, Megan Wei, Cedegao E. Zhang, Tan Zhi-Xuan, Adrian Weller, Joshua B. Tenenbaum, Lionel Wong:
The Neuro-Symbolic Inverse Planning Engine (NIPE): Modeling Probabilistic Social Inferences from Linguistic Inputs. CoRR abs/2306.14325 (2023) - [i91]Hector Zenil, Jesper Tegnér, Felipe S. Abrahão, Alexander Lavin, Vipin Kumar, Jeremy G. Frey, Adrian Weller, Larisa N. Soldatova, Alan R. Bundy, Nicholas R. Jennings, Koichi Takahashi, Lawrence Hunter, Saso Dzeroski, Andrew Briggs, Frederick D. Gregory, Carla P. Gomes, Christopher K. I. Williams, Jon Rowe, James A. Evans, Hiroaki Kitano, Joshua B. Tenenbaum, Ross D. King:
The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence. CoRR abs/2307.07522 (2023) - [i90]Matthew Barker, Emma Kallina, Dhananjay Ashok, Katherine M. Collins, Ashley Casovan, Adrian Weller, Ameet Talwalkar, Valerie Chen, Umang Bhatt:
FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines. CoRR abs/2307.15475 (2023) - [i89]Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T. Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu:
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models. CoRR abs/2309.12284 (2023) - [i88]Mateo Espinosa Zarlenga, Katherine M. Collins, Krishnamurthy Dvijotham, Adrian Weller, Zohreh Shams, Mateja Jamnik:
Learning to Receive Help: Intervention-Aware Concept Embedding Models. CoRR abs/2309.16928 (2023) - [i87]Victoria Smith, Ali Shahin Shamsabadi, Carolyn Ashurst, Adrian Weller:
Identifying and Mitigating Privacy Risks Stemming from Language Models: A Survey. CoRR abs/2310.01424 (2023) - [i86]Isaac Reid, Eli Berger, Krzysztof Choromanski, Adrian Weller:
Repelling Random Walks. CoRR abs/2310.04854 (2023) - [i85]Isaac Reid, Krzysztof Choromanski, Eli Berger, Adrian Weller:
Universal Graph Random Features. CoRR abs/2310.04859 (2023) - [i84]Yandong Wen, Weiyang Liu, Yao Feng, Bhiksha Raj, Rita Singh, Adrian Weller, Michael J. Black, Bernhard Schölkopf:
Pairwise Similarity Learning is SimPLE. CoRR abs/2310.09449 (2023) - [i83]Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, Andreea Bobu, Been Kim, Bradley C. Love, Erin Grant, Jascha Achterberg, Joshua B. Tenenbaum, Katherine M. Collins, Katherine L. Hermann, Kerem Oktar, Klaus Greff, Martin N. Hebart, Nori Jacoby, Qiuyi Zhang, Raja Marjieh, Robert Geirhos, Sherol Chen, Simon Kornblith, Sunayana Rane, Talia Konkle, Thomas P. O'Connell, Thomas Unterthiner, Andrew K. Lampinen, Klaus-Robert Müller, Mariya Toneva, Thomas L. Griffiths:
Getting aligned on representational alignment. CoRR abs/2310.13018 (2023) - [i82]Cedegao E. Zhang, Katherine M. Collins, Adrian Weller, Joshua B. Tenenbaum:
AI for Mathematics: A Cognitive Science Perspective. CoRR abs/2310.13021 (2023) - [i81]Matthew Ashman, Tommy Rochussen, Adrian Weller:
Amortised Inference in Neural Networks for Small-Scale Probabilistic Meta-Learning. CoRR abs/2310.15786 (2023) - [i80]Weiyang Liu, Zeju Qiu, Yao Feng, Yuliang Xiu, Yuxuan Xue, Longhui Yu, Haiwen Feng, Zhen Liu, Juyeon Heo, Songyou Peng, Yandong Wen, Michael J. Black, Adrian Weller, Bernhard Schölkopf:
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization. CoRR abs/2311.06243 (2023) - [i79]Matthew Wicker, Vihari Piratla, Adrian Weller:
Certification of Distributional Individual Fairness. CoRR abs/2311.11911 (2023) - [i78]Vihari Piratla, Juyeon Heo, Sukriti Singh, Adrian Weller:
Estimation of Concept Explanations Should be Uncertainty Aware. CoRR abs/2312.08063 (2023) - 2022
- [i77]Javier Abad Martinez, Umang Bhatt, Adrian Weller, Giovanni Cherubin:
Approximating Full Conformal Prediction at Scale via Influence Functions. CoRR abs/2202.01315 (2022) - [i76]Luca Viano, Yu-Ting Huang, Parameswaran Kamalaruban, Craig Innes, Subramanian Ramamoorthy, Adrian Weller:
Robust Learning from Observation with Model Misspecification. CoRR abs/2202.06003 (2022) - [i75]Matthew Ashman, Thang D. Bui, Cuong V. Nguyen, Efstratios Markou, Adrian Weller, Siddharth Swaroop, Richard E. Turner:
Partitioned Variational Inference: A Framework for Probabilistic Federated Learning. CoRR abs/2202.12275 (2022) - [i74]Varun Babbar, Umang Bhatt, Adrian Weller:
On the Utility of Prediction Sets in Human-AI Teams. CoRR abs/2205.01411 (2022) - [i73]James Jordon, Lukasz Szpruch, Florimond Houssiau, Mirko Bottarelli, Giovanni Cherubin, Carsten Maple, Samuel N. Cohen, Adrian Weller:
Synthetic Data - what, why and how? CoRR abs/2205.03257 (2022) - [i72]Valerie Chen, Umang Bhatt, Hoda Heidari, Adrian Weller, Ameet Talwalkar:
Perspectives on Incorporating Expert Feedback into Model Updates. CoRR abs/2205.06905 (2022) - [i71]Isabel Chien, Nina Deliu, Richard E. Turner, Adrian Weller, Sofia S. Villar, Niki Kilbertus:
Multi-disciplinary fairness considerations in machine learning for clinical trials. CoRR abs/2205.08875 (2022) - [i70]Miri Zilka, Holli Sargeant, Adrian Weller:
Transparency, Governance and Regulation of Algorithmic Tools Deployed in the Criminal Justice System: a UK Case Study. CoRR abs/2205.15258 (2022) - [i69]Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller:
Chefs' Random Tables: Non-Trigonometric Random Features. CoRR abs/2205.15317 (2022) - [i68]Vedant Nanda, Till Speicher, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Adrian Weller:
Measuring Representational Robustness of Neural Networks Through Shared Invariances. CoRR abs/2206.11939 (2022) - [i67]Katherine M. Collins, Umang Bhatt, Adrian Weller:
Eliciting and Learning with Soft Labels from Every Annotator. CoRR abs/2207.00810 (2022) - [i66]Weiyang Liu, Zhen Liu, Liam Paull, Adrian Weller, Bernhard Schölkopf:
Structural Causal 3D Reconstruction. CoRR abs/2207.10156 (2022) - [i65]Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Zohreh Shams, Frédéric Precioso, Stefano Melacci, Adrian Weller, Pietro Liò, Mateja Jamnik:
Concept Embedding Models. CoRR abs/2209.09056 (2022) - [i64]Darren Cook, Miri Zilka, Heidi DeSandre, Susan Giles, Adrian Weller, Simon Maskell:
Can We Automate the Analysis of Online Child Sexual Exploitation Discourse? CoRR abs/2209.12320 (2022) - [i63]Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, Weiyang Liu:
Continual Learning by Modeling Intra-Class Variation. CoRR abs/2210.05398 (2022) - [i62]Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf:
Iterative Teaching by Data Hallucination. CoRR abs/2210.17467 (2022) - [i61]Katherine M. Collins, Umang Bhatt, Weiyang Liu, Vihari Piratla, Bradley C. Love, Adrian Weller:
Web-based Elicitation of Human Perception on mixup Data. CoRR abs/2211.01202 (2022) - [i60]Sunghwan Joo, Seokhyeon Jeong, Juyeon Heo, Adrian Weller, Taesup Moon:
Towards More Robust Interpretation via Local Gradient Alignment. CoRR abs/2211.15900 (2022) - [i59]Matthew Wicker, Juyeon Heo, Luca Costabello, Adrian Weller:
Robust Explanation Constraints for Neural Networks. CoRR abs/2212.08507 (2022) - 2021
- [i58]Krzysztof Choromanski, Deepali Jain, Jack Parker-Holder, Xingyou Song, Valerii Likhosherstov, Anirban Santara, Aldo Pacchiano, Yunhao Tang, Adrian Weller:
Unlocking Pixels for Reinforcement Learning via Implicit Attention. CoRR abs/2102.04353 (2021) - [i57]Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller:
Learning with Hyperspherical Uniformity. CoRR abs/2103.01649 (2021) - [i56]Dan Ley, Umang Bhatt, Adrian Weller:
δ-CLUE: Diverse Sets of Explanations for Uncertainty Estimates. CoRR abs/2104.06323 (2021) - [i55]Dmitry Kazhdan, Botty Dimanov, Helena Andrés-Terré, Mateja Jamnik, Pietro Liò, Adrian Weller:
Is Disentanglement all you need? Comparing Concept-based & Disentanglement Approaches. CoRR abs/2104.06917 (2021) - [i54]Ahmad Khajehnejad, Moein Khajehnejad, Mahmoudreza Babaei, Krishna P. Gummadi, Adrian Weller, Baharan Mirzasoleiman:
CrossWalk: Fairness-enhanced Node Representation Learning. CoRR abs/2105.02725 (2021) - [i53]Andrei Margeloiu, Matthew Ashman, Umang Bhatt, Yanzhi Chen, Mateja Jamnik, Adrian Weller:
Do Concept Bottleneck Models Learn as Intended? CoRR abs/2105.04289 (2021) - [i52]Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Davis, Adrian Weller:
Debiasing a First-order Heuristic for Approximate Bi-level Optimization. CoRR abs/2106.02487 (2021) - [i51]Valerii Likhosherstov, Krzysztof Choromanski, Adrian Weller:
On the Expressive Power of Self-Attention Matrices. CoRR abs/2106.03764 (2021) - [i50]Umang Bhatt, Isabel Chien, Muhammad Bilal Zafar, Adrian Weller:
DIVINE: Diverse Influential Training Points for Data Visualization and Model Refinement. CoRR abs/2107.05978 (2021) - [i49]Yandong Wen, Weiyang Liu, Adrian Weller, Bhiksha Raj, Rita Singh:
SphereFace2: Binary Classification is All You Need for Deep Face Recognition. CoRR abs/2108.01513 (2021) - [i48]Weiyang Liu, Yandong Wen, Bhiksha Raj, Rita Singh, Adrian Weller:
SphereFace Revived: Unifying Hyperspherical Face Recognition. CoRR abs/2109.05565 (2021) - [i47]Krzysztof Choromanski, Haoxian Chen, Han Lin, Yuanzhe Ma, Arijit Sehanobish, Deepali Jain, Michael S. Ryoo, Jake Varley, Andy Zeng, Valerii Likhosherstov, Dmitry Kalashnikov, Vikas Sindhwani, Adrian Weller:
Hybrid Random Features. CoRR abs/2110.04367 (2021) - [i46]Weiyang Liu, Zhen Liu, Hanchen Wang, Liam Paull, Bernhard Schölkopf, Adrian Weller:
Iterative Teaching by Label Synthesis. CoRR abs/2110.14432 (2021) - [i45]Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuangsheng Zheng, Jianming Wang, Zhen Li, Carola-Bibiane Schönlieb, Tian Xia:
Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence. CoRR abs/2111.09461 (2021) - [i44]Valerii Likhosherstov, Anurag Arnab, Krzysztof Choromanski, Mario Lucic, Yi Tay, Adrian Weller, Mostafa Dehghani:
PolyViT: Co-training Vision Transformers on Images, Videos and Audio. CoRR abs/2111.12993 (2021) - [i43]Hanlin Zhang, Yi-Fan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric P. Xing:
Towards Principled Disentanglement for Domain Generalization. CoRR abs/2111.13839 (2021) - [i42]Vedant Nanda, Ayan Majumdar, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Bradley C. Love, Adrian Weller:
Exploring Alignment of Representations with Human Perception. CoRR abs/2111.14726 (2021) - [i41]Dan Ley, Umang Bhatt, Adrian Weller:
Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates. CoRR abs/2112.02646 (2021) - [i40]Shahar Avin, Haydn Belfield, Miles Brundage, Gretchen Krueger, Jasmine Wang, Adrian Weller, Markus Anderljung, Igor Krawczuk, David Krueger, Jonathan Lebensold, Tegan Maharaj, Noa Zilberman:
Filling gaps in trustworthy development of AI. CoRR abs/2112.07773 (2021) - 2020
- [i39]Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamás Sarlós, Adrian Weller, Vikas Sindhwani:
Stochastic Flows and Geometric Optimization on the Orthogonal Group. CoRR abs/2003.13563 (2020) - [i38]Miles Brundage, Shahar Avin, Jasmine Wang, Haydn Belfield, Gretchen Krueger, Gillian K. Hadfield, Heidy Khlaaf, Jingying Yang, Helen Toner, Ruth Fong, Tegan Maharaj, Pang Wei Koh, Sara Hooker, Jade Leung, Andrew Trask, Emma Bluemke, Jonathan Lebensold, Cullen O'Keefe, Mark Koren, Théo Ryffel, J. B. Rubinovitz, Tamay Besiroglu, Federica Carugati, Jack Clark, Peter Eckersley, Sarah de Haas, Maritza Johnson, Ben Laurie, Alex Ingerman, Igor Krawczuk, Amanda Askell, Rosario Cammarota, Andrew Lohn, David Krueger, Charlotte Stix, Peter Henderson, Logan Graham, Carina Prunkl, Bianca Martin, Elizabeth Seger, Noa Zilberman, Seán Ó hÉigeartaigh, Frens Kroeger, Girish Sastry, Rebecca Kagan, Adrian Weller, Brian Tse, Elizabeth Barnes, Allan Dafoe, Paul Scharre, Ariel Herbert-Voss, Martijn Rasser, Shagun Sodhani, Carrick Flynn, Thomas Krendl Gilbert, Lisa Dyer, Saif Khan, Yoshua Bengio, Markus Anderljung:
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. CoRR abs/2004.07213 (2020) - [i37]Valerii Likhosherstov, Jared Davis, Krzysztof Choromanski, Adrian Weller:
CWY Parametrization for Scalable Learning of Orthogonal and Stiefel Matrices. CoRR abs/2004.08675 (2020) - [i36]Umang Bhatt, Adrian Weller, José M. F. Moura:
Evaluating and Aggregating Feature-based Model Explanations. CoRR abs/2005.00631 (2020) - [i35]Nina Grgic-Hlaca, Adrian Weller, Elissa M. Redmiles:
Dimensions of Diversity in Human Perceptions of Algorithmic Fairness. CoRR abs/2005.00808 (2020) - [i34]Jared Quincy Davis, Krzysztof Choromanski, Jake Varley, Honglak Lee, Jean-Jacques E. Slotine, Valerii Likhosterov, Adrian Weller, Ameesh Makadia, Vikas Sindhwani:
Time Dependence in Non-Autonomous Neural ODEs. CoRR abs/2005.01906 (2020) - [i33]Moein Khajehnejad, Ahmad Asgharian Rezaei, Mahmoudreza Babaei, Jessica Hoffmann, Mahdi Jalili, Adrian Weller:
Adversarial Graph Embeddings for Fair Influence Maximization over Social Networks. CoRR abs/2005.04074 (2020) - [i32]Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Jared Davis, Tamás Sarlós, David Belanger, Lucy J. Colwell, Adrian Weller:
Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers. CoRR abs/2006.03555 (2020) - [i31]Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Davis, Adrian Weller:
UFO-BLO: Unbiased First-Order Bilevel Optimization. CoRR abs/2006.03631 (2020) - [i30]Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández-Lobato:
Getting a CLUE: A Method for Explaining Uncertainty Estimates. CoRR abs/2006.06848 (2020) - [i29]Krzysztof Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani:
An Ode to an ODE. CoRR abs/2006.11421 (2020) - [i28]Umang Bhatt, McKane Andrus, Adrian Weller, Alice Xiang:
Machine Learning Explainability for External Stakeholders. CoRR abs/2007.05408 (2020) - [i27]Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamás Sarlós, Peter Hawkins, Jared Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy J. Colwell, Adrian Weller:
Rethinking Attention with Performers. CoRR abs/2009.14794 (2020) - [i26]Julius von Kügelgen, Umang Bhatt, Amir-Hossein Karimi, Isabel Valera, Adrian Weller, Bernhard Schölkopf:
On the Fairness of Causal Algorithmic Recourse. CoRR abs/2010.06529 (2020) - [i25]Dmitry Kazhdan, Botty Dimanov, Mateja Jamnik, Pietro Liò, Adrian Weller:
Now You See Me (CME): Concept-based Model Extraction. CoRR abs/2010.13233 (2020) - [i24]Umang Bhatt, Yunfeng Zhang, Javier Antorán, Q. Vera Liao, Prasanna Sattigeri, Riccardo Fogliato, Gabrielle Gauthier Melançon, Ranganath Krishnan, Jason Stanley, Omesh Tickoo, Lama Nachman, Rumi Chunara, Adrian Weller, Alice Xiang:
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. CoRR abs/2011.07586 (2020) - [i23]Andrei Margeloiu, Nikola Simidjievski, Mateja Jamnik, Adrian Weller:
Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training. CoRR abs/2012.01166 (2020) - [i22]Valerii Likhosherstov, Krzysztof Choromanski, Jared Davis, Xingyou Song, Adrian Weller:
Sub-Linear Memory: How to Make Performers SLiM. CoRR abs/2012.11346 (2020) - 2019
- [i21]Mark Rowland, Jiri Hron, Yunhao Tang, Krzysztof Choromanski, Tamás Sarlós, Adrian Weller:
Orthogonal Estimation of Wasserstein Distances. CoRR abs/1903.03784 (2019) - [i20]Yunfei Teng, Wenbo Gao, François Chalus, Anna Choromanska, Donald Goldfarb, Adrian Weller:
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models. CoRR abs/1905.10395 (2019) - [i19]Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva:
The Sensitivity of Counterfactual Fairness to Unmeasured Confounding. CoRR abs/1907.01040 (2019) - [i18]Umang Bhatt, Alice Xiang, Shubham Sharma, Adrian Weller, Ankur Taly, Yunhan Jia, Joydeep Ghosh, Ruchir Puri, José M. F. Moura, Peter Eckersley:
Explainable Machine Learning in Deployment. CoRR abs/1909.06342 (2019) - [i17]Julius von Kügelgen, Paul K. Rubenstein, Bernhard Schölkopf, Adrian Weller:
Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks. CoRR abs/1910.03962 (2019) - [i16]Hanchen Wang, Nina Grgic-Hlaca, Preethi Lahoti, Krishna P. Gummadi, Adrian Weller:
An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision. CoRR abs/1910.10255 (2019) - [i15]Michiel A. Bakker, Duy Patrick Tu, Humberto Riverón Valdés, Krishna P. Gummadi, Kush R. Varshney, Adrian Weller, Alex Pentland:
DADI: Dynamic Discovery of Fair Information with Adversarial Reinforcement Learning. CoRR abs/1910.13983 (2019) - 2018
- [i14]Nina Grgic-Hlaca, Elissa M. Redmiles, Krishna P. Gummadi, Adrian Weller:
Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction. CoRR abs/1802.09548 (2018) - [i13]Krzysztof Choromanski, Mark Rowland, Vikas Sindhwani, Richard E. Turner, Adrian Weller:
Structured Evolution with Compact Architectures for Scalable Policy Optimization. CoRR abs/1804.02395 (2018) - [i12]Niki Kilbertus, Adrià Gascón, Matt J. Kusner, Michael Veale, Krishna P. Gummadi, Adrian Weller:
Blind Justice: Fairness with Encrypted Sensitive Attributes. CoRR abs/1806.03281 (2018) - [i11]Till Speicher, Hoda Heidari, Nina Grgic-Hlaca, Krishna P. Gummadi, Adish Singla, Adrian Weller, Muhammad Bilal Zafar:
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices. CoRR abs/1807.00787 (2018) - [i10]Been Kim, Kush R. Varshney, Adrian Weller:
Proceedings of the 2018 ICML Workshop on Human Interpretability in Machine Learning (WHI 2018). CoRR abs/1807.01308 (2018) - 2017
- [i9]Matej Balog, Nilesh Tripuraneni, Zoubin Ghahramani, Adrian Weller:
Lost Relatives of the Gumbel Trick. CoRR abs/1706.04161 (2017) - [i8]Nina Grgic-Hlaca, Muhammad Bilal Zafar, Krishna P. Gummadi, Adrian Weller:
On Fairness, Diversity and Randomness in Algorithmic Decision Making. CoRR abs/1706.10208 (2017) - [i7]Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez-Rodriguez, Krishna P. Gummadi, Adrian Weller:
From Parity to Preference-based Notions of Fairness in Classification. CoRR abs/1707.00010 (2017) - [i6]Adrian Weller:
Challenges for Transparency. CoRR abs/1708.01870 (2017) - [i5]Been Kim, Dmitry M. Malioutov, Kush R. Varshney, Adrian Weller:
Proceedings of the 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017). CoRR abs/1708.02666 (2017) - 2015
- [i4]Adrian Weller, Justin Domke:
Clamping Improves TRW and Mean Field Approximations. CoRR abs/1510.00087 (2015) - 2014
- [i3]Adrian Weller, Tony Jebara:
Approximating the Bethe partition function. CoRR abs/1401.0044 (2014) - 2013
- [i2]Adrian Weller, Tony Jebara:
Bethe Bounds and Approximating the Global Optimum. CoRR abs/1301.0015 (2013) - [i1]Adrian Weller, Tony Jebara:
On MAP Inference by MWSS on Perfect Graphs. CoRR abs/1309.6872 (2013)
Coauthor Index
[j8] [j5] [c113] [c109] [c108] [c107] [c105] [c103] [c99] [c85] [c83] [c82] [c81] [c72] [c67] [c61] [c57] [c54] [c47] [c44] [c43] [c41] [i122] [i121] [i116] [i114] [i110] [i104] [i100] [i99] [i95] [i93] [i90] [i77] [i74] [i72] [i67] [i62] [i61] [i56] [i53] [i50] [i41] [i36] [i30] [i28] [i26] [i24] [i18]
Krzysztof Choromanski
aka: Krzysztof Marcin Choromanski
aka: Krzysztof Marcin Choromanski
Jared Davis
aka: Jared Quincy Davis
aka: Jared Quincy Davis
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