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ORCIDKilian Q. Weinberger
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- affiliation: Department of Computer Science and Engineering, Washington University in St. Louis
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2020 – today
- 2022
[c96]Felix Wu, Kwangyoun Kim, Jing Pan, Kyu J. Han, Kilian Q. Weinberger, Yoav Artzi:
Performance-Efficiency Trade-Offs in Unsupervised Pre-Training for Speech Recognition. ICASSP 2022: 7667-7671- [i74]Boyi Li, Kilian Q. Weinberger, Serge J. Belongie, Vladlen Koltun, René Ranftl:
Language-driven Semantic Segmentation. CoRR abs/2201.03546 (2022) - [i73]Ruihan Wu, Jin Peng Zhou, Kilian Q. Weinberger, Chuan Guo:
Does Label Differential Privacy Prevent Label Inference Attacks? CoRR abs/2202.12968 (2022) - [i72]Yurong You, Katie Z. Luo, Xiangyu Chen, Junan Chen, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception. CoRR abs/2203.11405 (2022) - [i71]Yurong You, Katie Z. Luo, Cheng Perng Phoo, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Learning to Detect Mobile Objects from LiDAR Scans Without Labels. CoRR abs/2203.15882 (2022) - [i70]Felix Wu, Kwangyoun Kim, Shinji Watanabe, Kyu J. Han, Ryan McDonald, Kilian Q. Weinberger, Yoav Artzi:
Wav2Seq: Pre-training Speech-to-Text Encoder-Decoder Models Using Pseudo Languages. CoRR abs/2205.01086 (2022) - [i69]Ramya Ramakrishnan, Hashan Buddhika Narangodage, Mauro Schilman, Kilian Q. Weinberger, Ryan McDonald:
Long-term Control for Dialogue Generation: Methods and Evaluation. CoRR abs/2205.07352 (2022) - [i68]Ruihan Wu, Xin Yang, Yuanshun Yao, Jiankai Sun, Tianyi Liu, Kilian Q. Weinberger, Chong Wang:
Differentially Private Multi-Party Data Release for Linear Regression. CoRR abs/2206.07998 (2022) - 2021
- [c95]Johan Bjorck, Anmol Kabra, Kilian Q. Weinberger, Carla P. Gomes:
Characterizing the Loss Landscape in Non-Negative Matrix Factorization. AAAI 2021: 6768-6776 - [c94]Johan Bjorck, Kilian Q. Weinberger, Carla P. Gomes:
Understanding Decoupled and Early Weight Decay. AAAI 2021: 6777-6785 - [c93]Boyi Li, Felix Wu, Ser-Nam Lim, Serge J. Belongie, Kilian Q. Weinberger:
On Feature Normalization and Data Augmentation. CVPR 2021: 12383-12392 - [c92]Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, Ser-Nam Lim:
Deep Co-Training with Task Decomposition for Semi-Supervised Domain Adaptation. ICCV 2021: 8886-8896 - [c91]Tianyi Zhang, Felix Wu, Arzoo Katiyar, Kilian Q. Weinberger, Yoav Artzi:
Revisiting Few-sample BERT Fine-tuning. ICLR 2021 - [c90]Johan Björck, Xiangyu Chen, Christopher De Sa, Carla P. Gomes, Kilian Q. Weinberger:
Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision. ICML 2021: 980-991 - [c89]Ruihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens van der Maaten, Kilian Q. Weinberger:
Making Paper Reviewing Robust to Bid Manipulation Attacks. ICML 2021: 11240-11250 - [c88]Johan Bjorck, Carla P. Gomes, Kilian Q. Weinberger:
Towards Deeper Deep Reinforcement Learning with Spectral Normalization. NeurIPS 2021: 8242-8255 - [c87]Ruihan Wu, Chuan Guo, Yi Su, Kilian Q. Weinberger:
Online Adaptation to Label Distribution Shift. NeurIPS 2021: 11340-11351 - [i67]Ruihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens van der Maaten, Kilian Q. Weinberger:
Making Paper Reviewing Robust to Bid Manipulation Attacks. CoRR abs/2102.06020 (2021) - [i66]Johan Bjorck, Xiangyu Chen, Christopher De Sa, Carla P. Gomes, Kilian Q. Weinberger:
Low-Precision Reinforcement Learning. CoRR abs/2102.13565 (2021) - [i65]Yurong You, Carlos Andres Diaz-Ruiz, Yan Wang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger:
Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection. CoRR abs/2103.14198 (2021) - [i64]Johan Bjorck, Carla P. Gomes, Kilian Q. Weinberger:
Towards Deeper Deep Reinforcement Learning. CoRR abs/2106.01151 (2021) - [i63]Ruihan Wu, Chuan Guo, Yi Su, Kilian Q. Weinberger:
Online Adaptation to Label Distribution Shift. CoRR abs/2107.04520 (2021) - [i62]Felix Wu, Kwangyoun Kim, Jing Pan, Kyu J. Han, Kilian Q. Weinberger, Yoav Artzi:
Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition. CoRR abs/2109.06870 (2021) - [i61]Johan Bjorck, Carla P. Gomes, Kilian Q. Weinberger:
Is High Variance Unavoidable in RL? A Case Study in Continuous Control. CoRR abs/2110.11222 (2021) - [i60]Cole Miles, Rhine Samajdar, Sepehr Ebadi, Tout T. Wang, Hannes Pichler, Subir Sachdev, Mikhail D. Lukin, Markus Greiner, Kilian Q. Weinberger, Eun-Ah Kim:
Machine learning discovery of new phases in programmable quantum simulator snapshots. CoRR abs/2112.10789 (2021) - 2020
- [c86]Rui Qian, Divyansh Garg, Yan Wang, Yurong You, Serge J. Belongie
, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection. CVPR 2020: 5880-5889 - [c85]Yan Wang, Xiangyu Chen, Yurong You, Li Erran Li, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
Train in Germany, Test in the USA: Making 3D Object Detectors Generalize. CVPR 2020: 11710-11720 - [c84]Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving. ICLR 2020 - [c83]Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, Yoav Artzi:
BERTScore: Evaluating Text Generation with BERT. ICLR 2020 - [c82]Divyansh Garg, Yan Wang, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
Wasserstein Distances for Stereo Disparity Estimation. NeurIPS 2020 - [c81]Geoff Pleiss, Tianyi Zhang, Ethan R. Elenberg, Kilian Q. Weinberger:
Identifying Mislabeled Data using the Area Under the Margin Ranking. NeurIPS 2020 - [i59]Gao Huang, Zhuang Liu, Geoff Pleiss, Laurens van der Maaten, Kilian Q. Weinberger:
Convolutional Networks with Dense Connectivity. CoRR abs/2001.02394 (2020) - [i58]Geoff Pleiss, Tianyi Zhang, Ethan R. Elenberg, Kilian Q. Weinberger:
Identifying Mislabeled Data using the Area Under the Margin Ranking. CoRR abs/2001.10528 (2020) - [i57]Wei-Lun Chao, Han-Jia Ye, De-Chuan Zhan, Mark E. Campbell, Kilian Q. Weinberger:
Revisiting Meta-Learning as Supervised Learning. CoRR abs/2002.00573 (2020) - [i56]Chuan Guo, Ruihan Wu, Kilian Q. Weinberger:
TrojanNet: Embedding Hidden Trojan Horse Models in Neural Networks. CoRR abs/2002.10078 (2020) - [i55]Boyi Li, Felix Wu, Ser-Nam Lim, Serge J. Belongie, Kilian Q. Weinberger:
On Feature Normalization and Data Augmentation. CoRR abs/2002.11102 (2020) - [i54]Rui Qian, Divyansh Garg, Yan Wang, Yurong You, Serge J. Belongie, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection. CoRR abs/2004.03080 (2020) - [i53]Yan Wang, Xiangyu Chen, Yurong You, Li Erran Li, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
Train in Germany, Test in The USA: Making 3D Object Detectors Generalize. CoRR abs/2005.08139 (2020) - [i52]Tianyi Zhang, Felix Wu, Arzoo Katiyar, Kilian Q. Weinberger, Yoav Artzi:
Revisiting Few-sample BERT Fine-tuning. CoRR abs/2006.05987 (2020) - [i51]Divyansh Garg, Yan Wang, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
Wasserstein Distances for Stereo Disparity Estimation. CoRR abs/2007.03085 (2020) - [i50]Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, Ser-Nam Lim:
MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation. CoRR abs/2007.12684 (2020) - [i49]Cole Miles, Annabelle Bohrdt, Ruihan Wu, Christie Chiu, Muqing Xu, Geoffrey Ji, Markus Greiner, Kilian Q. Weinberger, Eugene Demler, Eun-Ah Kim:
Correlator Convolutional Neural Networks: An Interpretable Architecture for Image-like Quantum Matter Data. CoRR abs/2011.03474 (2020) - [i48]Johan Bjorck, Kilian Q. Weinberger, Carla P. Gomes:
Understanding Decoupled and Early Weight Decay. CoRR abs/2012.13841 (2020)
2010 – 2019
- 2019
- [j10]Brian H. Wang, Wei-Lun Chao, Yan Wang, Bharath Hariharan, Kilian Q. Weinberger, Mark Campbell:
LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images. IEEE Robotics Autom. Lett. 4(3): 2902-2909 (2019) - [c80]Carlos Diaz-Ruiz, Yan Wang, Wei-Lun Chao, Kilian Q. Weinberger, Mark E. Campbell:
Vision-only 3D Tracking for Self-Driving Cars. CASE 2019: 1029-1034 - [c79]Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving. CVPR 2019: 8445-8453 - [c78]Chuan Guo, Jacob R. Gardner, Yurong You, Andrew Gordon Wilson, Kilian Q. Weinberger:
Simple Black-box Adversarial Attacks. ICML 2019: 2484-2493 - [c77]Felix Wu, Amauri H. Souza Jr., Tianyi Zhang, Christopher Fifty, Tao Yu, Kilian Q. Weinberger:
Simplifying Graph Convolutional Networks. ICML 2019: 6861-6871 - [c76]Yan Wang, Zihang Lai, Gao Huang, Brian H. Wang, Laurens van der Maaten, Mark E. Campbell, Kilian Q. Weinberger:
Anytime Stereo Image Depth Estimation on Mobile Devices. ICRA 2019: 5893-5900 - [c75]Boyi Li, Felix Wu, Kilian Q. Weinberger, Serge J. Belongie:
Positional Normalization. NeurIPS 2019: 1620-1632 - [c74]Shengyuan Hu, Tao Yu, Chuan Guo, Wei-Lun Chao, Kilian Q. Weinberger:
A New Defense Against Adversarial Images: Turning a Weakness into a Strength. NeurIPS 2019: 1633-1644 - [c73]Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew Gordon Wilson:
Exact Gaussian Processes on a Million Data Points. NeurIPS 2019: 14622-14632 - [c72]Chuan Guo, Jared S. Frank, Kilian Q. Weinberger:
Low Frequency Adversarial Perturbation. UAI 2019: 1127-1137 - [i47]Zhixiang Eddie Xu, Gao Huang, Kilian Q. Weinberger, Alice X. Zheng:
Gradient Boosted Feature Selection. CoRR abs/1901.04055 (2019) - [i46]Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Alice X. Zheng:
Gradient Regularized Budgeted Boosting. CoRR abs/1901.04065 (2019) - [i45]Felix Wu, Tianyi Zhang, Amauri H. Souza Jr., Christopher Fifty, Tao Yu, Kilian Q. Weinberger:
Simplifying Graph Convolutional Networks. CoRR abs/1902.07153 (2019) - [i44]Felix Wu, Boyi Li, Lequn Wang, Ni Lao, John Blitzer, Kilian Q. Weinberger:
FastFusionNet: New State-of-the-Art for DAWNBench SQuAD. CoRR abs/1902.11291 (2019) - [i43]Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew Gordon Wilson:
Exact Gaussian Processes on a Million Data Points. CoRR abs/1903.08114 (2019) - [i42]Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, Yoav Artzi:
BERTScore: Evaluating Text Generation with BERT. CoRR abs/1904.09675 (2019) - [i41]Chuan Guo, Jacob R. Gardner, Yurong You, Andrew Gordon Wilson, Kilian Q. Weinberger:
Simple Black-box Adversarial Attacks. CoRR abs/1905.07121 (2019) - [i40]Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving. CoRR abs/1906.06310 (2019) - [i39]Boyi Li, Felix Wu, Kilian Q. Weinberger, Serge J. Belongie:
Positional Normalization. CoRR abs/1907.04312 (2019) - [i38]Felix Wu, Boyi Li, Lequn Wang, Ni Lao, John Blitzer, Kilian Q. Weinberger:
Integrated Triaging for Fast Reading Comprehension. CoRR abs/1909.13128 (2019) - [i37]Tao Yu, Shengyuan Hu, Chuan Guo, Wei-Lun Chao, Kilian Q. Weinberger:
A New Defense Against Adversarial Images: Turning a Weakness into a Strength. CoRR abs/1910.07629 (2019) - [i36]Brian H. Wang, Wei-Lun Chao, Yan Wang, Bharath Hariharan, Kilian Q. Weinberger, Mark E. Campbell:
LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images. CoRR abs/1910.13955 (2019) - [i35]Yan Wang, Wei-Lun Chao, Kilian Q. Weinberger, Laurens van der Maaten:
SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning. CoRR abs/1911.04623 (2019) - 2018
- [j9]Sheila A. McIlraith, Kilian Q. Weinberger, G. Michael Youngblood, Karen L. Myers, Eric Eaton, Michael Wollowski:
A Recap of the AAAI and IAAI 2018 Conferences and the EAAI Symposium. AI Mag. 39(4): 3-16 (2018) - [j8]Xilun Chen, Yu Sun, Ben Athiwaratkun, Claire Cardie, Kilian Q. Weinberger:
Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification. Trans. Assoc. Comput. Linguistics 6: 557-570 (2018) - [c71]Jacob R. Gardner, Geoff Pleiss, Ruihan Wu, Kilian Q. Weinberger, Andrew Gordon Wilson:
Product Kernel Interpolation for Scalable Gaussian Processes. AISTATS 2018: 1407-1416 - [c70]Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger:
CondenseNet: An Efficient DenseNet Using Learned Group Convolutions. CVPR 2018: 2752-2761 - [c69]Yan Wang, Lequn Wang, Yurong You, Xu Zou, Vincent Chen, Serena Li, Gao Huang, Bharath Hariharan, Kilian Q. Weinberger:
Resource Aware Person Re-Identification Across Multiple Resolutions. CVPR 2018: 8042-8051 - [c68]Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, Kilian Q. Weinberger:
Multi-Scale Dense Networks for Resource Efficient Image Classification. ICLR 2018 - [c67]Geoff Pleiss, Jacob R. Gardner, Kilian Q. Weinberger, Andrew Gordon Wilson:
Constant-Time Predictive Distributions for Gaussian Processes. ICML 2018: 4111-4120 - [c66]Jacob R. Gardner, Geoff Pleiss, Kilian Q. Weinberger, David Bindel, Andrew Gordon Wilson:
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration. NeurIPS 2018: 7587-7597 - [c65]Johan Bjorck, Carla P. Gomes, Bart Selman, Kilian Q. Weinberger:
Understanding Batch Normalization. NeurIPS 2018: 7705-7716 - [e6]Sheila A. McIlraith, Kilian Q. Weinberger:
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-18), New Orleans, Louisiana, USA, February 2-7, 2018. AAAI Press 2018 [contents] - [i34]Jacob R. Gardner, Geoff Pleiss, Ruihan Wu, Kilian Q. Weinberger, Andrew Gordon Wilson:
Product Kernel Interpolation for Scalable Gaussian Processes. CoRR abs/1802.08903 (2018) - [i33]Geoff Pleiss, Jacob R. Gardner, Kilian Q. Weinberger, Andrew Gordon Wilson:
Constant-Time Predictive Distributions for Gaussian Processes. CoRR abs/1803.06058 (2018) - [i32]Yan Wang, Lequn Wang, Yurong You, Xu Zou, Vincent Chen, Serena Li, Gao Huang, Bharath Hariharan, Kilian Q. Weinberger:
Resource Aware Person Re-identification across Multiple Resolutions. CoRR abs/1805.08805 (2018) - [i31]Qiantong Xu, Gao Huang, Yang Yuan, Chuan Guo, Yu Sun, Felix Wu, Kilian Q. Weinberger:
An empirical study on evaluation metrics of generative adversarial networks. CoRR abs/1806.07755 (2018) - [i30]Chuan Guo, Jared S. Frank, Kilian Q. Weinberger:
Low Frequency Adversarial Perturbation. CoRR abs/1809.08758 (2018) - [i29]Jacob R. Gardner, Geoff Pleiss, David Bindel, Kilian Q. Weinberger, Andrew Gordon Wilson:
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration. CoRR abs/1809.11165 (2018) - [i28]Brian H. Wang, Yan Wang, Kilian Q. Weinberger, Mark Campbell:
Deep Person Re-identification for Probabilistic Data Association in Multiple Pedestrian Tracking. CoRR abs/1810.08565 (2018) - [i27]Yan Wang, Zihang Lai, Gao Huang, Brian H. Wang, Laurens van der Maaten, Mark Campbell, Kilian Q. Weinberger:
Anytime Stereo Image Depth Estimation on Mobile Devices. CoRR abs/1810.11408 (2018) - [i26]Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving. CoRR abs/1812.07179 (2018) - 2017
- [c64]Jacob R. Gardner, Chuan Guo, Kilian Q. Weinberger, Roman Garnett, Roger B. Grosse:
Discovering and Exploiting Additive Structure for Bayesian Optimization. AISTATS 2017: 1311-1319 - [c63]Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger:
Densely Connected Convolutional Networks. CVPR 2017: 2261-2269 - [c62]Paul Upchurch, Jacob R. Gardner, Geoff Pleiss, Robert Pless, Noah Snavely, Kavita Bala, Kilian Q. Weinberger:
Deep Feature Interpolation for Image Content Changes. CVPR 2017: 6090-6099 - [c61]Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Q. Weinberger:
Snapshot Ensembles: Train 1, Get M for Free. ICLR (Poster) 2017 - [c60]Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger:
On Calibration of Modern Neural Networks. ICML 2017: 1321-1330 - [c59]Geoff Pleiss, Manish Raghavan, Felix Wu, Jon M. Kleinberg, Kilian Q. Weinberger:
On Fairness and Calibration. NIPS 2017: 5680-5689 - [i25]Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, Kilian Q. Weinberger:
Multi-Scale Dense Convolutional Networks for Efficient Prediction. CoRR abs/1703.09844 (2017) - [i24]Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Q. Weinberger:
Snapshot Ensembles: Train 1, get M for free. CoRR abs/1704.00109 (2017) - [i23]Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger:
On Calibration of Modern Neural Networks. CoRR abs/1706.04599 (2017) - [i22]Geoff Pleiss, Danlu Chen, Gao Huang, Tongcheng Li, Laurens van der Maaten, Kilian Q. Weinberger:
Memory-Efficient Implementation of DenseNets. CoRR abs/1707.06990 (2017) - [i21]Geoff Pleiss, Manish Raghavan, Felix Wu, Jon M. Kleinberg, Kilian Q. Weinberger:
On Fairness and Calibration. CoRR abs/1709.02012 (2017) - [i20]Felix Wu, Ni Lao, John Blitzer, Guandao Yang, Kilian Q. Weinberger:
Fast Reading Comprehension with ConvNets. CoRR abs/1711.04352 (2017) - [i19]Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger:
CondenseNet: An Efficient DenseNet using Learned Group Convolutions. CoRR abs/1711.09224 (2017) - 2016
- [c58]Matt J. Kusner, Yu Sun, Karthik Sridharan, Kilian Q. Weinberger:
Private Causal Inference. AISTATS 2016: 1308-1317 - [c57]Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Q. Weinberger:
Deep Networks with Stochastic Depth. ECCV (4) 2016: 646-661 - [c56]Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen:
Compressing Convolutional Neural Networks in the Frequency Domain. KDD 2016: 1475-1484 - [c55]Gao Huang, Chuan Guo, Matt J. Kusner, Yu Sun, Fei Sha, Kilian Q. Weinberger:
Supervised Word Mover's Distance. NIPS 2016: 4862-4870 - [e5]Maria-Florina Balcan, Kilian Q. Weinberger:
Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016. JMLR Workshop and Conference Proceedings 48, JMLR.org 2016 [contents] - [i18]Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Q. Weinberger:
Deep Networks with Stochastic Depth. CoRR abs/1603.09382 (2016) - [i17]Xilun Chen, Ben Athiwaratkun, Yu Sun, Kilian Q. Weinberger, Claire Cardie:
Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification. CoRR abs/1606.01614 (2016) - [i16]Gao Huang, Zhuang Liu, Kilian Q. Weinberger:
Densely Connected Convolutional Networks. CoRR abs/1608.06993 (2016) - [i15]Paul Upchurch, Jacob R. Gardner, Kavita Bala, Robert Pless, Noah Snavely, Kilian Q. Weinberger:
Deep Feature Interpolation for Image Content Changes. CoRR abs/1611.05507 (2016) - 2015
- [j7]Minmin Chen, Kilian Q. Weinberger, Zhixiang Eddie Xu, Fei Sha:
Marginalizing stacked linear denoising autoencoders. J. Mach. Learn. Res. 16: 3849-3875 (2015) - [c54]Zheng Chen, Minmin Chen, Kilian Q. Weinberger, Weixiong Zhang:
Marginalized Denoising for Link Prediction and Multi-Label Learning. AAAI 2015: 1707-1713 - [c53]Quan Zhou, Wenlin Chen, Shiji Song, Jacob R. Gardner, Kilian Q. Weinberger, Yixin Chen:
A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing. AAAI 2015: 3210-3216 - [c52]Wenlin Chen, Yixin Chen, Kilian Q. Weinberger:
Filtered Search for Submodular Maximization with Controllable Approximation Bounds. AISTATS 2015 - [c51]Matt J. Kusner, Jacob R. Gardner, Roman Garnett, Kilian Q. Weinberger:
Differentially Private Bayesian Optimization. ICML 2015: 918-927 - [c50]Matt J. Kusner, Yu Sun, Nicholas I. Kolkin, Kilian Q. Weinberger:
From Word Embeddings To Document Distances. ICML 2015: 957-966 - [c49]Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen:
Compressing Neural Networks with the Hashing Trick. ICML 2015: 2285-2294 - [c48]Gustavo Malkomes, Matt J. Kusner, Wenlin Chen, Kilian Q. Weinberger, Benjamin Moseley:
Fast Distributed k-Center Clustering with Outliers on Massive Data. NIPS 2015: 1063-1071 - [c47]Jacob R. Gardner, Gustavo Malkomes, Roman Garnett, Kilian Q. Weinberger, Dennis L. Barbour, John P. Cunningham:
Bayesian Active Model Selection with an Application to Automated Audiometry. NIPS 2015: 2386-2394 - [c46]Jacob R. Gardner, Xinyu Song, Kilian Q. Weinberger, Dennis L. Barbour, John P. Cunningham:
Psychophysical Detection Testing with Bayesian Active Learning. UAI 2015: 286-295 - [i14]Zhixiang Eddie Xu, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger:
Compressed Support Vector Machines. CoRR abs/1501.06478 (2015) - [i13]Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen:
Compressing Neural Networks with the Hashing Trick. CoRR abs/1504.04788 (2015) - [i12]Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen:
Compressing Convolutional Neural Networks. CoRR abs/1506.04449 (2015) - [i11]Jacob R. Gardner, Matt J. Kusner, Yixuan Li, Paul Upchurch, Kilian Q. Weinberger, John E. Hopcroft:
Deep Manifold Traversal: Changing Labels with Convolutional Features. CoRR abs/1511.06421 (2015) - 2014
- [j6]Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, Olivier Chapelle:
Classifier cascades and trees for minimizing feature evaluation cost. J. Mach. Learn. Res. 15(1): 2113-2144 (2014) - [c45]