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Soheil Feizi
Soheil Feizi-Khankandi
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2020 – today
- 2024
- [c95]Samyadeep Basu, Shell Xu Hu, Daniela Massiceti, Soheil Feizi:
Strong Baselines for Parameter-Efficient Few-Shot Fine-Tuning. AAAI 2024: 11024-11031 - [c94]Neha Mukund Kalibhat, Kanika Narang, Hamed Firooz, Maziar Sanjabi, Soheil Feizi:
Measuring Self-Supervised Representation Quality for Downstream Classification Using Discriminative Features. AAAI 2024: 13031-13039 - [c93]Samyadeep Basu, Shell Xu Hu, Maziar Sanjabi, Daniela Massiceti, Soheil Feizi:
Distilling Knowledge from Text-to-Image Generative Models Improves Visio-Linguistic Reasoning in CLIP. EMNLP 2024: 6105-6113 - [c92]Soumya Suvra Ghosal, Samyadeep Basu, Soheil Feizi, Dinesh Manocha:
IntCoOp: Interpretability-Aware Vision-Language Prompt Tuning. EMNLP 2024: 19584-19601 - [c91]Mazda Moayeri
, Elham Tabassi
, Soheil Feizi
:
WorldBench: Quantifying Geographic Disparities in LLM Factual Recall. FAccT 2024: 1211-1228 - [c90]Samyadeep Basu, Nanxuan Zhao, Vlad I. Morariu, Soheil Feizi, Varun Manjunatha:
Localizing and Editing Knowledge In Text-to-Image Generative Models. ICLR 2024 - [c89]Keivan Rezaei, Mehrdad Saberi, Mazda Moayeri, Soheil Feizi:
PRIME: Prioritizing Interpretability in Failure Mode Extraction. ICLR 2024 - [c88]Mehrdad Saberi, Vinu Sankar Sadasivan, Keivan Rezaei, Aounon Kumar, Atoosa Malemir Chegini, Wenxiao Wang, Soheil Feizi:
Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks. ICLR 2024 - [c87]Shoumik Saha, Wenxiao Wang, Yigitcan Kaya, Soheil Feizi, Tudor Dumitras:
DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness. ICLR 2024 - [c86]Samyadeep Basu, Keivan Rezaei, Priyatham Kattakinda, Vlad I. Morariu, Nanxuan Zhao, Ryan A. Rossi, Varun Manjunatha, Soheil Feizi:
On Mechanistic Knowledge Localization in Text-to-Image Generative Models. ICML 2024 - [c85]Vinu Sankar Sadasivan, Shoumik Saha, Gaurang Sriramanan, Priyatham Kattakinda, Atoosa Malemir Chegini, Soheil Feizi:
Fast Adversarial Attacks on Language Models In One GPU Minute. ICML 2024 - [c84]Sriram Balasubramanian, Samyadeep Basu, Soheil Feizi:
Decomposing and Interpreting Image Representations via Text in ViTs Beyond CLIP. NeurIPS 2024 - [c83]Samyadeep Basu, Martin Grayson, Cecily Morrison, Besmira Nushi, Soheil Feizi, Daniela Massiceti:
Understanding Information Storage and Transfer in Multi-Modal Large Language Models. NeurIPS 2024 - [c82]Prajwal Singhania, Siddharth Singh, Shwai He, Soheil Feizi, Abhinav Bhatele:
Loki: Low-rank Keys for Efficient Sparse Attention. NeurIPS 2024 - [c81]Gaurang Sriramanan, Siddhant Bharti, Vinu Sankar Sadasivan, Shoumik Saha, Priyatham Kattakinda, Soheil Feizi:
LLM-Check: Investigating Detection of Hallucinations in Large Language Models. NeurIPS 2024 - [c80]Sahil Singla, Atoosa Malemir Chegini, Mazda Moayeri, Soheil Feizi:
Data-Centric Debugging: mitigating model failures via targeted image retrieval. WACV 2024: 63-74 - [i114]Vinu Sankar Sadasivan, Shoumik Saha, Gaurang Sriramanan, Priyatham Kattakinda, Atoosa Malemir Chegini, Soheil Feizi:
Fast Adversarial Attacks on Language Models In One GPU Minute. CoRR abs/2402.15570 (2024) - [i113]Hamid Kazemi, Atoosa Malemir Chegini, Jonas Geiping, Soheil Feizi, Tom Goldstein:
What do we learn from inverting CLIP models? CoRR abs/2403.02580 (2024) - [i112]Mazda Moayeri, Samyadeep Basu, Sriram Balasubramanian, Priyatham Kattakinda, Atoosa Malemir Chegini, Robert Brauneis, Soheil Feizi:
Rethinking Artistic Copyright Infringements in the Era of Text-to-Image Generative Models. CoRR abs/2404.08030 (2024) - [i111]Samyadeep Basu, Keivan Rezaei, Priyatham Kattakinda, Ryan A. Rossi, Cherry Zhao, Vlad I. Morariu, Varun Manjunatha, Soheil Feizi:
On Mechanistic Knowledge Localization in Text-to-Image Generative Models. CoRR abs/2405.01008 (2024) - [i110]Neha Mukund Kalibhat, Priyatham Kattakinda, Arman Zarei, Nikita Seleznev, Samuel Sharpe, Senthil Kumar, Soheil Feizi:
Understanding the Effect of using Semantically Meaningful Tokens for Visual Representation Learning. CoRR abs/2405.16401 (2024) - [i109]Sriram Balasubramanian, Samyadeep Basu, Soheil Feizi:
Decomposing and Interpreting Image Representations via Text in ViTs Beyond CLIP. CoRR abs/2406.01583 (2024) - [i108]Prajwal Singhania, Siddharth Singh, Shwai He, Soheil Feizi, Abhinav Bhatele:
Loki: Low-Rank Keys for Efficient Sparse Attention. CoRR abs/2406.02542 (2024) - [i107]Mehrdad Saberi, Vinu Sankar Sadasivan, Arman Zarei, Hessam Mahdavifar, Soheil Feizi:
DREW : Towards Robust Data Provenance by Leveraging Error-Controlled Watermarking. CoRR abs/2406.02836 (2024) - [i106]Samyadeep Basu, Martin Grayson, Cecily Morrison, Besmira Nushi, Soheil Feizi, Daniela Massiceti:
Understanding Information Storage and Transfer in Multi-modal Large Language Models. CoRR abs/2406.04236 (2024) - [i105]Arman Zarei, Keivan Rezaei, Samyadeep Basu, Mehrdad Saberi, Mazda Moayeri, Priyatham Kattakinda, Soheil Feizi:
Understanding and Mitigating Compositional Issues in Text-to-Image Generative Models. CoRR abs/2406.07844 (2024) - [i104]Donghyeon Joo, Ramyad Hadidi, Soheil Feizi, Bahar Asgari:
Endor: Hardware-Friendly Sparse Format for Offloaded LLM Inference. CoRR abs/2406.11674 (2024) - [i103]Soumya Suvra Ghosal, Samyadeep Basu, Soheil Feizi, Dinesh Manocha:
IntCoOp: Interpretability-Aware Vision-Language Prompt Tuning. CoRR abs/2406.13683 (2024) - [i102]Mihai Christodorescu, Ryan Craven, Soheil Feizi, Neil Gong, Mia Hoffmann, Somesh Jha, Zhengyuan Jiang, Mehrdad Saberi Kamarposhti, John C. Mitchell, Jessica Newman, Emelia Probasco, Yanjun Qi, Khawaja Shams, Matthew Turek:
Securing the Future of GenAI: Policy and Technology. CoRR abs/2407.12999 (2024) - [i101]Mazda Moayeri, Vidhisha Balachandran, Varun Chandrasekaran, Safoora Yousefi, Thomas Fel, Soheil Feizi, Besmira Nushi, Neel Joshi, Vibhav Vineet:
Unearthing Skill-Level Insights for Understanding Trade-Offs of Foundation Models. CoRR abs/2410.13826 (2024) - [i100]Keivan Rezaei, Khyathi Raghavi Chandu, Soheil Feizi, Yejin Choi, Faeze Brahman, Abhilasha Ravichander:
RESTOR: Knowledge Recovery through Machine Unlearning. CoRR abs/2411.00204 (2024) - [i99]Mihai Christodorescu, Ryan Craven, Soheil Feizi, Neil Zhenqiang Gong, Mia Hoffmann, Somesh Jha, Zhengyuan Jiang, Mehrdad Saberi Kamarposhti, John C. Mitchell, Jessica Newman, Emelia Probasco, Yanjun Qi, Khawaja Shams, Matthew Turek:
Securing the Future of GenAI: Policy and Technology. IACR Cryptol. ePrint Arch. 2024: 855 (2024) - 2023
- [j14]Clark W. Barrett, Brad Boyd, Elie Bursztein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang
, Florian Kerschbaum, Eric Mitchell, John C. Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang:
Identifying and Mitigating the Security Risks of Generative AI. Found. Trends Priv. Secur. 6(1): 1-52 (2023) - [j13]Chun Pong Lau
, Jiang Liu
, Hossein Souri
, Wei-An Lin
, Soheil Feizi
, Rama Chellappa
:
Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13054-13067 (2023) - [j12]Aya Abdelsalam Ismail, Sercan Ö. Arik, Jinsung Yoon, Ankur Taly, Soheil Feizi, Tomas Pfister:
Interpretable Mixture of Experts. Trans. Mach. Learn. Res. 2023 (2023) - [c79]Alexander Levine, Soheil Feizi:
Goal-Conditioned Q-learning as Knowledge Distillation. AAAI 2023: 8500-8509 - [c78]Neha Mukund Kalibhat, Samuel Sharpe, Jeremy Goodsitt, C. Bayan Bruss, Soheil Feizi:
Adapting Self-Supervised Representations to Multi-Domain Setups. BMVC 2023: 353-355 - [c77]Mazda Moayeri, Keivan Rezaei, Maziar Sanjabi, Soheil Feizi:
Text2Concept: Concept Activation Vectors Directly from Text. CVPR Workshops 2023: 3744-3749 - [c76]Vinu Sankar Sadasivan, Mahdi Soltanolkotabi
, Soheil Feizi:
CUDA: Convolution-Based Unlearnable Datasets. CVPR 2023: 3862-3871 - [c75]Sriram Balasubramanian, Soheil Feizi:
Towards Improved Input Masking for Convolutional Neural Networks. ICCV 2023: 1855-1865 - [c74]Samyadeep Basu, Megan Stanley, John Bronskill, Soheil Feizi, Daniela Massiceti:
Hard-Meta-Dataset++: Towards Understanding Few-Shot Performance on Difficult Tasks. ICLR 2023 - [c73]Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi:
Provable Robustness against Wasserstein Distribution Shifts via Input Randomization. ICLR 2023 - [c72]Yanchao Sun, Ruijie Zheng, Parisa Hassanzadeh, Yongyuan Liang, Soheil Feizi, Sumitra Ganesh, Furong Huang:
Certifiably Robust Policy Learning against Adversarial Multi-Agent Communication. ICLR 2023 - [c71]Neha Mukund Kalibhat, Shweta Bhardwaj, C. Bayan Bruss, Hamed Firooz, Maziar Sanjabi, Soheil Feizi:
Identifying Interpretable Subspaces in Image Representations. ICML 2023: 15623-15638 - [c70]Mazda Moayeri, Keivan Rezaei, Maziar Sanjabi, Soheil Feizi:
Text-To-Concept (and Back) via Cross-Model Alignment. ICML 2023: 25037-25060 - [c69]Keivan Rezaei, Kiarash Banihashem, Atoosa Malemir Chegini, Soheil Feizi:
Run-off Election: Improved Provable Defense against Data Poisoning Attacks. ICML 2023: 29030-29050 - [c68]Wenxiao Wang, Soheil Feizi:
Temporal Robustness against Data poisoning. NeurIPS 2023 - [c67]Sriram Balasubramanian, Gaurang Sriramanan, Vinu Sankar Sadasivan, Soheil Feizi:
Exploring Geometry of Blind Spots in Vision models. NeurIPS 2023 - [c66]Mazda Moayeri, Wenxiao Wang, Sahil Singla, Soheil Feizi:
Spuriosity Rankings: Sorting Data to Measure and Mitigate Biases. NeurIPS 2023 - [c65]Vedant Nanda, Till Speicher, John P. Dickerson, Krishna P. Gummadi, Soheil Feizi, Adrian Weller:
Diffused Redundancy in Pre-trained Representations. NeurIPS 2023 - [i98]Keivan Rezaei, Kiarash Banihashem, Atoosa Malemir Chegini, Soheil Feizi:
Run-Off Election: Improved Provable Defense against Data Poisoning Attacks. CoRR abs/2302.02300 (2023) - [i97]Wenxiao Wang, Soheil Feizi:
Temporal Robustness against Data Poisoning. CoRR abs/2302.03684 (2023) - [i96]Vinu Sankar Sadasivan, Mahdi Soltanolkotabi
, Soheil Feizi:
CUDA: Convolution-based Unlearnable Datasets. CoRR abs/2303.04278 (2023) - [i95]Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, Wenxiao Wang, Soheil Feizi:
Can AI-Generated Text be Reliably Detected? CoRR abs/2303.11156 (2023) - [i94]Shoumik Saha, Wenxiao Wang, Yigitcan Kaya, Soheil Feizi:
Adversarial Robustness of Learning-based Static Malware Classifiers. CoRR abs/2303.13372 (2023) - [i93]Aounon Kumar, Vinu Sankar Sadasivan, Soheil Feizi:
Provable Robustness for Streaming Models with a Sliding Window. CoRR abs/2303.16308 (2023) - [i92]Samyadeep Basu, Daniela Massiceti, Shell Xu Hu, Soheil Feizi:
Strong Baselines for Parameter Efficient Few-Shot Fine-tuning. CoRR abs/2304.01917 (2023) - [i91]Mazda Moayeri, Keivan Rezaei, Maziar Sanjabi, Soheil Feizi:
Text-To-Concept (and Back) via Cross-Model Alignment. CoRR abs/2305.06386 (2023) - [i90]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) - [i89]Wenxiao Wang, Soheil Feizi:
On Practical Aspects of Aggregation Defenses against Data Poisoning Attacks. CoRR abs/2306.16415 (2023) - [i88]Samyadeep Basu, Maziar Sanjabi, Daniela Massiceti, Shell Xu Hu, Soheil Feizi:
Augmenting CLIP with Improved Visio-Linguistic Reasoning. CoRR abs/2307.09233 (2023) - [i87]Neha Mukund Kalibhat, Shweta Bhardwaj, C. Bayan Bruss, Hamed Firooz, Maziar Sanjabi, Soheil Feizi:
Identifying Interpretable Subspaces in Image Representations. CoRR abs/2307.10504 (2023) - [i86]Clark W. Barrett, Brad Boyd, Ellie Burzstein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang, Florian Kerschbaum, Eric Mitchell, John C. Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang:
Identifying and Mitigating the Security Risks of Generative AI. CoRR abs/2308.14840 (2023) - [i85]Aounon Kumar, Chirag Agarwal, Suraj Srinivas, Soheil Feizi, Hima Lakkaraju:
Certifying LLM Safety against Adversarial Prompting. CoRR abs/2309.02705 (2023) - [i84]Neha Mukund Kalibhat, Samuel Sharpe, Jeremy Goodsitt, C. Bayan Bruss, Soheil Feizi:
Adapting Self-Supervised Representations to Multi-Domain Setups. CoRR abs/2309.03999 (2023) - [i83]Mehrdad Saberi, Vinu Sankar Sadasivan, Keivan Rezaei, Aounon Kumar, Atoosa Malemir Chegini, Wenxiao Wang, Soheil Feizi:
Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks. CoRR abs/2310.00076 (2023) - [i82]Keivan Rezaei, Mehrdad Saberi, Mazda Moayeri, Soheil Feizi:
PRIME: Prioritizing Interpretability in Failure Mode Extraction. CoRR abs/2310.00164 (2023) - [i81]Samyadeep Basu, Mehrdad Saberi, Shweta Bhardwaj, Atoosa Malemir Chegini, Daniela Massiceti, Maziar Sanjabi, Shell Xu Hu, Soheil Feizi:
EditVal: Benchmarking Diffusion Based Text-Guided Image Editing Methods. CoRR abs/2310.02426 (2023) - [i80]Samyadeep Basu, Nanxuan Zhao, Vlad I. Morariu, Soheil Feizi, Varun Manjunatha:
Localizing and Editing Knowledge in Text-to-Image Generative Models. CoRR abs/2310.13730 (2023) - [i79]Sriram Balasubramanian, Gaurang Sriramanan, Vinu Sankar Sadasivan, Soheil Feizi:
Exploring Geometry of Blind Spots in Vision Models. CoRR abs/2310.19889 (2023) - [i78]Soheil Feizi, MohammadTaghi Hajiaghayi, Keivan Rezaei, Suho Shin:
Online Advertisements with LLMs: Opportunities and Challenges. CoRR abs/2311.07601 (2023) - [i77]Jiang Liu, Chen Wei, Yuxiang Guo, Heng Yu, Alan L. Yuille, Soheil Feizi, Chun Pong Lau, Rama Chellappa:
Instruct2Attack: Language-Guided Semantic Adversarial Attacks. CoRR abs/2311.15551 (2023) - [i76]Atoosa Malemir Chegini, Soheil Feizi:
Identifying and Mitigating Model Failures through Few-shot CLIP-aided Diffusion Generation. CoRR abs/2312.05464 (2023) - 2022
- [j11]Jiang Liu
, Chun Pong Lau
, Hossein Souri, Soheil Feizi
, Rama Chellappa:
Mutual Adversarial Training: Learning Together is Better Than Going Alone. IEEE Trans. Inf. Forensics Secur. 17: 2364-2377 (2022) - [c64]Alexander Levine, Soheil Feizi:
Provable Adversarial Robustness for Fractional Lp Threat Models. AISTATS 2022: 9908-9942 - [c63]Jiang Liu, Alexander Levine, Chun Pong Lau
, Rama Chellappa, Soheil Feizi:
Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detection. CVPR 2022: 14953-14962 - [c62]Mazda Moayeri, Phillip Pope, Yogesh Balaji, Soheil Feizi:
A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes. CVPR 2022: 19065-19075 - [c61]Sahil Singla, Soheil Feizi:
Salient ImageNet: How to discover spurious features in Deep Learning? ICLR 2022 - [c60]Sahil Singla, Surbhi Singla, Soheil Feizi:
Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100. ICLR 2022 - [c59]Aounon Kumar, Alexander Levine, Soheil Feizi:
Policy Smoothing for Provably Robust Reinforcement Learning. ICLR 2022 - [c58]Priyatham Kattakinda
, Soheil Feizi:
FOCUS: Familiar Objects in Common and Uncommon Settings. ICML 2022: 10825-10847 - [c57]Wenxiao Wang, Alexander Levine, Soheil Feizi:
Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation. ICML 2022: 22769-22783 - [c56]Wenxiao Wang, Alexander Levine, Soheil Feizi:
Lethal Dose Conjecture on Data Poisoning. NeurIPS 2022 - [c55]Sahil Singla, Soheil Feizi:
Improved techniques for deterministic l2 robustness. NeurIPS 2022 - [c54]Mazda Moayeri, Sahil Singla, Soheil Feizi:
Hard ImageNet: Segmentations for Objects with Strong Spurious Cues. NeurIPS 2022 - [c53]Mazda Moayeri, Kiarash Banihashem, Soheil Feizi:
Explicit Tradeoffs between Adversarial and Natural Distributional Robustness. NeurIPS 2022 - [c52]Gaurang Sriramanan, Maharshi Gor, Soheil Feizi:
Toward Efficient Robust Training against Union of $\ell_p$ Threat Models. NeurIPS 2022 - [i75]Mazda Moayeri, Phillip Pope, Yogesh Balaji, Soheil Feizi:
A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes. CoRR abs/2201.10766 (2022) - [i74]Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi:
Certifying Model Accuracy under Distribution Shifts. CoRR abs/2201.12440 (2022) - [i73]Wenxiao Wang, Alexander Levine, Soheil Feizi:
Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation. CoRR abs/2202.02628 (2022) - [i72]Neha Mukund Kalibhat, Kanika Narang, Liang Tan, Hamed Firooz, Maziar Sanjabi, Soheil Feizi:
Understanding Failure Modes of Self-Supervised Learning. CoRR abs/2203.01881 (2022) - [i71]Alexander Levine, Soheil Feizi:
Provable Adversarial Robustness for Fractional Lp Threat Models. CoRR abs/2203.08945 (2022) - [i70]Sahil Singla, Mazda Moayeri, Soheil Feizi:
Core Risk Minimization using Salient ImageNet. CoRR abs/2203.15566 (2022) - [i69]Aya Abdelsalam Ismail, Sercan Ö. Arik, Jinsung Yoon, Ankur Taly, Soheil Feizi, Tomas Pfister:
Interpretable Mixture of Experts for Structured Data. CoRR abs/2206.02107 (2022) - [i68]Yanchao Sun, Ruijie Zheng, Parisa Hassanzadeh, Yongyuan Liang, Soheil Feizi, Sumitra Ganesh, Furong Huang:
Certifiably Robust Policy Learning against Adversarial Communication in Multi-agent Systems. CoRR abs/2206.10158 (2022) - [i67]Wenxiao Wang, Alexander Levine, Soheil Feizi:
Lethal Dose Conjecture on Data Poisoning. CoRR abs/2208.03309 (2022) - [i66]Alexander Levine, Soheil Feizi:
Goal-Conditioned Q-Learning as Knowledge Distillation. CoRR abs/2208.13298 (2022) - [i65]Mazda Moayeri, Kiarash Banihashem, Soheil Feizi:
Explicit Tradeoffs between Adversarial and Natural Distributional Robustness. CoRR abs/2209.07592 (2022) - [i64]Sahil Singla, Soheil Feizi:
Improved techniques for deterministic l2 robustness. CoRR abs/2211.08453 (2022) - [i63]Sahil Singla, Atoosa Malemir Chegini, Mazda Moayeri, Soheil Feizi:
Data-Centric Debugging: mitigating model failures via targeted data collection. CoRR abs/2211.09859 (2022) - [i62]Priyatham Kattakinda, Alexander Levine, Soheil Feizi:
Invariant Learning via Diffusion Dreamed Distribution Shifts. CoRR abs/2211.10370 (2022) - [i61]Sriram Balasubramanian, Soheil Feizi:
Towards Better Input Masking for Convolutional Neural Networks. CoRR abs/2211.14646 (2022) - [i60]Mazda Moayeri, Wenxiao Wang, Sahil Singla, Soheil Feizi:
Spuriosity Rankings: Sorting Data for Spurious Correlation Robustness. CoRR abs/2212.02648 (2022) - 2021
- [c51]Neha Mukund Kalibhat, Yogesh Balaji, Soheil Feizi:
Winning Lottery Tickets in Deep Generative Models. AAAI 2021: 8038-8046 - [c50]Mucong Ding, Constantinos Daskalakis, Soheil Feizi:
GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences. AISTATS 2021: 3709-3717 - [c49]Vedant Nanda, Samuel Dooley, Sahil Singla, Soheil Feizi, John P. Dickerson:
Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning. FAccT 2021: 466-477 - [c48]Mazda Moayeri, Soheil Feizi:
Sample Efficient Detection and Classification of Adversarial Attacks via Self-Supervised Embeddings. ICCV 2021: 7657-7666 - [c47]Vasu Singla, Sahil Singla, Soheil Feizi, David Jacobs:
Low Curvature Activations Reduce Overfitting in Adversarial Training. ICCV 2021: 16403-16413 - [c46]Alexander Levine, Soheil Feizi:
Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks. ICLR 2021 - [c45]Sahil Singla, Soheil Feizi:
Fantastic Four: Differentiable and Efficient Bounds on Singular Values of Convolution Layers. ICLR 2021 - [c44]Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi
, Soheil Feizi:
Understanding Over-parameterization in Generative Adversarial Networks. ICLR 2021 - [c43]Samyadeep Basu, Phillip Pope, Soheil Feizi:
Influence Functions in Deep Learning Are Fragile. ICLR 2021 - [c42]Cassidy Laidlaw, Sahil Singla, Soheil Feizi:
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models. ICLR 2021 - [c41]Alexander Levine, Soheil Feizi:
Improved, Deterministic Smoothing for L1 Certified Robustness. ICML 2021: 6254-6264 - [c40]Sahil Singla, Soheil Feizi:
Skew Orthogonal Convolutions. ICML 2021: 9756-9766 - [c39]Aya Abdelsalam Ismail, Héctor Corrada Bravo, Soheil Feizi:
Improving Deep Learning Interpretability by Saliency Guided Training. NeurIPS 2021: 26726-26739 - [c38]Gowthami Somepalli, Yexin Wu, Yogesh Balaji, Bhanukiran Vinzamuri, Soheil Feizi:
Unsupervised anomaly detection with adversarial mirrored autoencoders. UAI 2021: 365-375 - [i59]Vasu Singla, Sahil Singla, David Jacobs, Soheil Feizi:
Low Curvature Activations Reduce Overfitting in Adversarial Training. CoRR abs/2102.07861 (2021) - [i58]Alexander Levine, Soheil Feizi:
Improved, Deterministic Smoothing for L1 Certified Robustness. CoRR abs/2103.10834 (2021) - [i57]Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi:
Understanding Overparameterization in Generative Adversarial Networks. CoRR abs/2104.05605 (2021) - [i56]Sahil Singla, Soheil Feizi:
Skew Orthogonal Convolutions. CoRR abs/2105.11417 (2021) - [i55]Aounon Kumar, Alexander Levine, Soheil Feizi:
Policy Smoothing for Provably Robust Reinforcement Learning. CoRR abs/2106.11420 (2021)