Weinberger, Kilian Q.

88 publications

NeurIPS 2025 $Q\sharp$: Provably Optimal Distributional RL for LLM Post-Training Jin Peng Zhou, Kaiwen Wang, Jonathan Daniel Chang, Zhaolin Gao, Nathan Kallus, Kilian Q Weinberger, Kianté Brantley, Wen Sun

ICLR 2025 Learning 3D Perception from Others' Predictions Jinsu Yoo, Zhenyang Feng, Tai-Yu Pan, Yihong Sun, Cheng Perng Phoo, Xiangyu Chen, Mark Campbell, Kilian Q Weinberger, Bharath Hariharan, Wei-Lun Chao

ICLRW 2025 Leveraging Large Language Models to Repair High-Level Robot Controllers from Assumption Violations Qian Meng, Jin Peng Zhou, Kilian Q Weinberger, Hadas Kress-Gazit

ICCV 2025 Mixed Signals: A Diverse Point Cloud Dataset for Heterogeneous LiDAR V2X Collaboration Katie Z Luo, Minh-Quan Dao, Zhenzhen Liu, Mark Campbell, Wei-Lun Chao, Kilian Q Weinberger, Ezio Malis, Vincent Fremont, Bharath Hariharan, Mao Shan, Stewart Worrall, Julie Stephany Berrio Perez

ICLR 2025 On Speeding up Language Model Evaluation Jin Peng Zhou, Christian K Belardi, Ruihan Wu, Travis Zhang, Carla P Gomes, Wen Sun, Kilian Q Weinberger

ICML 2025 PhantomWiki: On-Demand Datasets for Reasoning and Retrieval Evaluation Albert Gong, Kamilė Stankevičiūtė, Chao Wan, Anmol Kabra, Raphael Thesmar, Johann Lee, Julius Klenke, Carla P Gomes, Kilian Q Weinberger

ICLRW 2025 PhantomWiki: On-Demand Datasets for Reasoning and Retrieval Evaluation Albert Gong, Kamilė Stankevičiūtė, Chao Wan, Anmol Kabra, Raphael Thesmar, Johann Lee, Julius Klenke, Carla P Gomes, Kilian Q Weinberger

ICLR 2025 Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond Qizhou Wang, Jin Peng Zhou, Zhanke Zhou, Saebyeol Shin, Bo Han, Kilian Q Weinberger

CVPR 2025 Transfer Your Perspective: Controllable 3D Generation from Any Viewpoint in a Driving Scene Tai-Yu Pan, Sooyoung Jeon, Mengdi Fan, Jinsu Yoo, Zhenyang Feng, Mark Campbell, Kilian Q. Weinberger, Bharath Hariharan, Wei-Lun Chao

NeurIPS 2024 DiffuBox: Refining 3D Object Detection with Point Diffusion Xiangyu Chen, Zhenzhen Liu, Katie Z Luo, Siddhartha Datta, Adhitya Polavaram, Yan Wang, Yurong You, Boyi Li, Marco Pavone, Wei-Lun Chao, Mark Campbell, Bharath Hariharan, Kilian Q. Weinberger

ICLR 2024 Don't Trust: Verify -- Grounding LLM Quantitative Reasoning with Autoformalization Jin Peng Zhou, Charles E Staats, Wenda Li, Christian Szegedy, Kilian Q Weinberger, Yuhuai Wu

NeurIPS 2024 Online Feature Updates Improve Online (Generalized) Label Shift Adaptation Ruihan Wu, Siddhartha Datta, Yi Su, Dheeraj Baby, Yu-Xiang Wang, Kilian Q. Weinberger

ICLR 2024 Pre-Training LiDAR-Based 3D Object Detectors Through Colorization Tai-Yu Pan, Chenyang Ma, Tianle Chen, Cheng Perng Phoo, Katie Z Luo, Yurong You, Mark Campbell, Kilian Q Weinberger, Bharath Hariharan, Wei-Lun Chao

AISTATS 2023 Does Label Differential Privacy Prevent Label Inference Attacks? Ruihan Wu, Jin Peng Zhou, Kilian Q. Weinberger, Chuan Guo

ICML 2023 IncDSI: Incrementally Updatable Document Retrieval Varsha Kishore, Chao Wan, Justin Lovelace, Yoav Artzi, Kilian Q Weinberger

NeurIPS 2023 Latent Diffusion for Language Generation Justin Lovelace, Varsha Kishore, Chao Wan, Eliot Shekhtman, Kilian Q. Weinberger

ICLR 2023 Learning Iterative Neural Optimizers for Image Steganography Xiangyu Chen, Varsha Kishore, Kilian Q Weinberger

UAI 2023 Learning to Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning Ruihan Wu, Xiangyu Chen, Chuan Guo, Kilian Q. Weinberger

ICML 2023 On the Effectiveness of Offline RL for Dialogue Response Generation Paloma Sodhi, Felix Wu, Ethan R. Elenberg, Kilian Q Weinberger, Ryan Mcdonald

NeurIPS 2023 Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery Katie Luo, Zhenzhen Liu, Xiangyu Chen, Yurong You, Sagie Benaim, Cheng Perng Phoo, Mark Campbell, Wen Sun, Bharath Hariharan, Kilian Q. Weinberger

ICCVW 2023 Unsupervised Domain Adaptation for Self-Driving from past Traversal Features Travis Zhang, Katie Luo, Cheng Perng Phoo, Yurong You, Wei-Lun Chao, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger

ICML 2023 Unsupervised Out-of-Distribution Detection with Diffusion Inpainting Zhenzhen Liu, Jin Peng Zhou, Yufan Wang, Kilian Q Weinberger

ICLR 2022 Fixed Neural Network Steganography: Train the Images, Not the Network Varsha Kishore, Xiangyu Chen, Yan Wang, Boyi Li, Kilian Q Weinberger

ICLR 2022 Hindsight Is 20/20: Leveraging past Traversals to Aid 3D Perception Yurong You, Katie Z Luo, Xiangyu Chen, Junan Chen, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark Campbell, Kilian Q Weinberger

ICLR 2022 Is High Variance Unavoidable in RL? a Case Study in Continuous Control Johan Bjorck, Carla P Gomes, Kilian Q Weinberger

CVPR 2022 Ithaca365: Dataset and Driving Perception Under Repeated and Challenging Weather Conditions Carlos A. Diaz-Ruiz, Youya Xia, Yurong You, Jose Nino, Junan Chen, Josephine Monica, Xiangyu Chen, Katie Luo, Yan Wang, Marc Emond, Wei-Lun Chao, Bharath Hariharan, Kilian Q. Weinberger, Mark Campbell

ICLR 2022 Language-Driven Semantic Segmentation Boyi Li, Kilian Q Weinberger, Serge Belongie, Vladlen Koltun, Rene Ranftl

CVPR 2022 Learning to Detect Mobile Objects from LiDAR Scans Without Labels Yurong You, Katie Luo, Cheng Perng Phoo, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger

NeurIPS 2022 Unsupervised Adaptation from Repeated Traversals for Autonomous Driving Yurong You, Cheng Perng Phoo, Katie Luo, Travis Zhang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger

AAAI 2021 Characterizing the Loss Landscape in Non-Negative Matrix Factorization Johan Bjorck, Anmol Kabra, Kilian Q. Weinberger, Carla P. Gomes

ICCV 2021 Deep Co-Training with Task Decomposition for Semi-Supervised Domain Adaptation Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, Ser-Nam Lim

CVPR 2021 On Feature Normalization and Data Augmentation Boyi Li, Felix Wu, Ser-Nam Lim, Serge Belongie, Kilian Q. Weinberger

NeurIPS 2021 Online Adaptation to Label Distribution Shift Ruihan Wu, Chuan Guo, Yi Su, Kilian Q. Weinberger

ICLR 2021 Revisiting Few-Sample BERT Fine-Tuning Tianyi Zhang, Felix Wu, Arzoo Katiyar, Kilian Q Weinberger, Yoav Artzi

NeurIPS 2021 Towards Deeper Deep Reinforcement Learning with Spectral Normalization Nils Bjorck, Carla P. Gomes, Kilian Q. Weinberger

AAAI 2021 Understanding Decoupled and Early Weight Decay Johan Bjorck, Kilian Q. Weinberger, Carla P. Gomes

ICLR 2020 BERTScore: Evaluating Text Generation with BERT Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, Yoav Artzi

NeurIPS 2020 Identifying Mislabeled Data Using the Area Under the Margin Ranking Geoff Pleiss, Tianyi Zhang, Ethan Elenberg, Kilian Q. Weinberger

ICLR 2020 Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger

ICLR 2020 TrojanNet: Exposing the Danger of Trojan Horse Attack on Neural Networks Chuan Guo, Ruihan Wu, Kilian Q. Weinberger

NeurIPS 2020 Wasserstein Distances for Stereo Disparity Estimation Divyansh Garg, Yan Wang, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao

ICMLW 2019 A Meta Understanding of Meta-Learning Wei-Lun Chao, Han-Jia Ye, De-Chuan Zhan, Mark Campbell, Kilian Q. Weinberger

NeurIPS 2019 A New Defense Against Adversarial Images: Turning a Weakness into a Strength Shengyuan Hu, Tao Yu, Chuan Guo, Wei-Lun Chao, Kilian Q. Weinberger

NeurIPS 2019 Exact Gaussian Processes on a Million Data Points Ke Wang, Geoff Pleiss, Jacob Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew Gordon Wilson

UAI 2019 Low Frequency Adversarial Perturbation Chuan Guo, Jared S. Frank, Kilian Q. Weinberger

NeurIPS 2019 Positional Normalization Boyi Li, Felix Wu, Kilian Q. Weinberger, Serge Belongie

NeurIPS 2018 GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration Jacob Gardner, Geoff Pleiss, Kilian Q. Weinberger, David Bindel, Andrew G Wilson

AAAI 2018 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 Sheila A. McIlraith, Kilian Q. Weinberger

AISTATS 2018 Product Kernel Interpolation for Scalable Gaussian Processes Jacob R. Gardner, Geoff Pleiss, Ruihan Wu, Kilian Q. Weinberger, Andrew Gordon Wilson

NeurIPS 2018 Understanding Batch Normalization Nils Bjorck, Carla P. Gomes, Bart Selman, Kilian Q. Weinberger

CVPR 2017 Densely Connected Convolutional Networks Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger

AISTATS 2017 Discovering and Exploiting Additive Structure for Bayesian Optimization Jacob R. Gardner, Chuan Guo, Kilian Q. Weinberger, Roman Garnett, Roger B. Grosse

ICML 2017 On Calibration of Modern Neural Networks Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger

NeurIPS 2017 On Fairness and Calibration Geoff Pleiss, Manish Raghavan, Felix Wu, Jon Kleinberg, Kilian Q. Weinberger

ICLR 2017 Snapshot Ensembles: Train 1, Get M for Free Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Q. Weinberger

ECCV 2016 Deep Networks with Stochastic Depth Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Q. Weinberger

AISTATS 2016 Private Causal Inference Matt J. Kusner, Yu Sun, Karthik Sridharan, Kilian Q. Weinberger

NeurIPS 2016 Supervised Word Mover's Distance Gao Huang, Chuan Guo, Matt J Kusner, Yu Sun, Fei Sha, Kilian Q. Weinberger

AAAI 2015 A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing Quan Zhou, Wenlin Chen, Shiji Song, Jacob R. Gardner, Kilian Q. Weinberger, Yixin Chen

NeurIPS 2015 Bayesian Active Model Selection with an Application to Automated Audiometry Jacob Gardner, Gustavo Malkomes, Roman Garnett, Kilian Q. Weinberger, Dennis Barbour, John P. Cunningham

NeurIPS 2015 Fast Distributed K-Center Clustering with Outliers on Massive Data Gustavo Malkomes, Matt J Kusner, Wenlin Chen, Kilian Q. Weinberger, Benjamin Moseley

AISTATS 2015 Filtered Search for Submodular Maximization with Controllable Approximation Bounds Wenlin Chen, Yixin Chen, Kilian Q. Weinberger

AAAI 2015 Marginalized Denoising for Link Prediction and Multi-Label Learning Zheng Chen, Minmin Chen, Kilian Q. Weinberger, Weixiong Zhang

JMLR 2015 Marginalizing Stacked Linear Denoising Autoencoders Minmin Chen, Kilian Q. Weinberger, Zhixiang Xu, Fei Sha

UAI 2015 Psychophysical Detection Testing with Bayesian Active Learning Jacob R. Gardner, Xinyu Song, Kilian Q. Weinberger, Dennis L. Barbour, John P. Cunningham

JMLR 2014 Classifier Cascades and Trees for Minimizing Feature Evaluation Cost Zhixiang Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, Olivier Chapelle

AAAI 2014 Feature-Cost Sensitive Learning with Submodular Trees of Classifiers Matt J. Kusner, Wenlin Chen, Quan Zhou, Zhixiang Eddie Xu, Kilian Q. Weinberger, Yixin Chen

ECML-PKDD 2014 Transductive Minimax Probability Machine Gao Huang, Shiji Song, Zhixiang Eddie Xu, Kilian Q. Weinberger

AAAI 2013 Goal-Oriented Euclidean Heuristics with Manifold Learning Wenlin Chen, Yixin Chen, Kilian Q. Weinberger, Qiang Lu, Xiaoping Chen

ICML 2012 Marginalized Denoising Autoencoders for Domain Adaptation Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha

NeurIPS 2012 Non-Linear Metric Learning Dor Kedem, Stephen Tyree, Fei Sha, Gert R. Lanckriet, Kilian Q. Weinberger

ICML 2012 The Greedy Miser: Learning Under Test-Time Budgets Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle

ICML 2011 Automatic Feature Decomposition for Single View Co-Training Minmin Chen, Kilian Q. Weinberger, Yixin Chen

MLJ 2011 Boosted Multi-Task Learning Olivier Chapelle, Pannagadatta K. Shivaswamy, Srinivas Vadrevu, Kilian Q. Weinberger, Ya Zhang, Belle L. Tseng

NeurIPS 2011 Co-Training for Domain Adaptation Minmin Chen, Kilian Q. Weinberger, John Blitzer

NeurIPS 2010 Decoding Ipsilateral Finger Movements from ECoG Signals in Humans Yuzong Liu, Mohit Sharma, Charles Gaona, Jonathan Breshears, Jarod Roland, Zachary Freudenburg, Eric Leuthardt, Kilian Q. Weinberger

NeurIPS 2010 Large Margin Multi-Task Metric Learning Shibin Parameswaran, Kilian Q. Weinberger

JMLR 2009 Distance Metric Learning for Large Margin Nearest Neighbor Classification Kilian Q. Weinberger, Lawrence K. Saul

ICML 2009 Feature Hashing for Large Scale Multitask Learning Kilian Q. Weinberger, Anirban Dasgupta, John Langford, Alexander J. Smola, Josh Attenberg

ICML 2008 Fast Solvers and Efficient Implementations for Distance Metric Learning Kilian Q. Weinberger, Lawrence K. Saul

NeurIPS 2008 Large Margin Taxonomy Embedding for Document Categorization Kilian Q. Weinberger, Olivier Chapelle

AISTATS 2007 Metric Learning for Kernel Regression Kilian Q. Weinberger, Gerald Tesauro

AAAI 2006 An Introduction to Nonlinear Dimensionality Reduction by Maximum Variance Unfolding Kilian Q. Weinberger, Lawrence K. Saul

NeurIPS 2006 Graph Laplacian Regularization for Large-Scale Semidefinite Programming Kilian Q. Weinberger, Fei Sha, Qihui Zhu, Lawrence K. Saul

NeurIPS 2005 Distance Metric Learning for Large Margin Nearest Neighbor Classification Kilian Q. Weinberger, John Blitzer, Lawrence K. Saul

NeurIPS 2004 Hierarchical Distributed Representations for Statistical Language Modeling John Blitzer, Fernando Pereira, Kilian Q. Weinberger, Lawrence K. Saul

ICML 2004 Learning a Kernel Matrix for Nonlinear Dimensionality Reduction Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul

CVPR 2004 Unsupervised Learning of Image Manifolds by Semidefinite Programming Kilian Q. Weinberger, Lawrence K. Saul