Salakhutdinov, Ruslan

211 publications

ICLRW 2025 Adaptively-Labeled Vision Datasets via Instance-Level Retrieval Brandon Trabucco, Rishav Mukherji, Yutong Bai, Ruslan Salakhutdinov

NeurIPS 2025 AgentDAM: Privacy Leakage Evaluation for Autonomous Web Agents Arman Zharmagambetov, Chuan Guo, Ivan Evtimov, Maya Pavlova, Ruslan Salakhutdinov, Kamalika Chaudhuri

TMLR 2025 Automated Black-Box Prompt Engineering for Personalized Text-to-Image Generation Yutong He, Alexander Robey, Naoki Murata, Yiding Jiang, Joshua Nathaniel Williams, George J. Pappas, Hamed Hassani, Yuki Mitsufuji, Ruslan Salakhutdinov, J Zico Kolter

ICML 2025 Optimizing Test-Time Compute via Meta Reinforcement Finetuning Yuxiao Qu, Matthew Y. R. Yang, Amrith Setlur, Lewis Tunstall, Edward Emanuel Beeching, Ruslan Salakhutdinov, Aviral Kumar

ICLRW 2025 Optimizing Test-Time Compute via Meta Reinforcement Finetuning Yuxiao Qu, Matthew Y. R. Yang, Amrith Setlur, Lewis Tunstall, Edward Emanuel Beeching, Ruslan Salakhutdinov, Aviral Kumar

ICLRW 2025 Optimizing Test-Time Compute via Meta Reinforcement Finetuning Yuxiao Qu, Matthew Y. R. Yang, Lewis Tunstall, Edward Emanuel Beeching, Ruslan Salakhutdinov

NeurIPS 2025 Retrospective In-Context Learning for Temporal Credit Assignment with Large Language Models Wentse Chen, Jiayu Chen, Fahim Tajwar, Hao Zhu, Xintong Duan, Ruslan Salakhutdinov, Jeff Schneider

TMLR 2025 State Combinatorial Generalization in Decision Making with Conditional Diffusion Models Xintong Duan, Yutong He, Fahim Tajwar, Wentse Chen, Ruslan Salakhutdinov, Jeff Schneider

ICLRW 2025 Towards Internet-Scale Training for Agents Brandon Trabucco, Gunnar A Sigurdsson, Robinson Piramuthu, Ruslan Salakhutdinov

ICLRW 2025 Training a Generally Curious Agent Fahim Tajwar, Yiding Jiang, Abitha Thankaraj, Sumaita Sadia Rahman, J Zico Kolter, Jeff Schneider, Ruslan Salakhutdinov

TMLR 2025 Tree Search for Language Model Agents Jing Yu Koh, Stephen Marcus McAleer, Daniel Fried, Ruslan Salakhutdinov

ICLR 2024 Confronting Reward Model Overoptimization with Constrained RLHF Ted Moskovitz, Aaditya K Singh, Dj Strouse, Tuomas Sandholm, Ruslan Salakhutdinov, Anca Dragan, Stephen Marcus McAleer

ICLR 2024 Contrastive Difference Predictive Coding Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach

ICLR 2024 Effective Data Augmentation with Diffusion Models Brandon Trabucco, Kyle Doherty, Max A Gurinas, Ruslan Salakhutdinov

NeurIPS 2024 HEMM: Holistic Evaluation of Multimodal Foundation Models Paul Pu Liang, Akshay Goindani, Talha Chafekar, Leena Mathur, Haofei Yu, Ruslan Salakhutdinov, Louis-Philippe Morency

NeurIPS 2024 Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference Benjamin Eysenbach, Vivek Myers, Ruslan Salakhutdinov, Sergey Levine

ICLR 2024 Manifold Preserving Guided Diffusion Yutong He, Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Dongjun Kim, Wei-Hsiang Liao, Yuki Mitsufuji, J Zico Kolter, Ruslan Salakhutdinov, Stefano Ermon

ECCV 2024 OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Web Raghav Kapoor, Yash Parag Butala, Melisa A Russak, Jing Yu Koh, Kiran Kamble, Waseem AlShikh, Ruslan Salakhutdinov

ICLR 2024 Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks Murtaza Dalal, Tarun Chiruvolu, Devendra Singh Chaplot, Ruslan Salakhutdinov

ICLRW 2024 Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks Murtaza Dalal, Tarun Chiruvolu, Devendra Singh Chaplot, Ruslan Salakhutdinov

ECCV 2024 Situated Instruction Following So Yeon Min, Xavier Puig, Devendra Singh Chaplot, Tsung-Yen Yang, Priyam Parashar, Akshara Rai, Ruslan Salakhutdinov, Yonatan Bisk, Roozbeh Mottaghi

ICLR 2024 Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data Chongyi Zheng, Benjamin Eysenbach, Homer Rich Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine

NeurIPS 2024 Stylus: Automatic Adapter Selection for Diffusion Models Michael Luo, Justin Wong, Brandon Trabucco, Yanping Huang, Joseph E. Gonzalez, Zhifeng Chen, Ruslan Salakhutdinov, Ion Stoica

ICLRW 2024 VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks Jing Yu Koh, Robert Lo, Lawrence Jang, Vikram Duvvur, Ming Chong Lim, Po-Yu Huang, Graham Neubig, Shuyan Zhou, Ruslan Salakhutdinov, Daniel Fried

ICML 2023 A Connection Between One-Step RL and Critic Regularization in Reinforcement Learning Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov

ICLR 2023 A Simple Approach for Visual Room Rearrangement: 3D Mapping and Semantic Search Brandon Trabucco, Gunnar A Sigurdsson, Robinson Piramuthu, Gaurav S. Sukhatme, Ruslan Salakhutdinov

NeurIPSW 2023 Confronting Reward Model Overoptimization with Constrained RLHF Ted Moskovitz, Aaditya Singh, Dj Strouse, Tuomas Sandholm, Ruslan Salakhutdinov, Anca Dragan, Stephen McAleer

NeurIPSW 2023 Contrastive Difference Predictive Coding Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach

L4DC 2023 Contrastive Example-Based Control Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn

NeurIPSW 2023 Contrastive Representations Make Planning Easy Benjamin Eysenbach, Vivek Myers, Sergey Levine, Ruslan Salakhutdinov

ICMLW 2023 Distributional Distance Classifiers for Goal-Conditioned Reinforcement Learning Ravi Tej Akella, Benjamin Eysenbach, Jeff Schneider, Ruslan Salakhutdinov

ICLRW 2023 Effective Data Augmentation with Diffusion Models Brandon Trabucco, Kyle Doherty, Max Gurinas, Ruslan Salakhutdinov

NeurIPSW 2023 Effective Data Augmentation with Diffusion Models Brandon Trabucco, Kyle Doherty, Max Gurinas, Ruslan Salakhutdinov

NeurIPSW 2023 Effective Data Augmentation with Diffusion Models Brandon Trabucco, Kyle Doherty, Max Gurinas, Ruslan Salakhutdinov

NeurIPS 2023 Factorized Contrastive Learning: Going Beyond Multi-View Redundancy Paul Pu Liang, Zihao Deng, Martin Q. Ma, James Y Zou, Louis-Philippe Morency, Ruslan Salakhutdinov

NeurIPS 2023 Generating Images with Multimodal Language Models Jing Yu Koh, Daniel Fried, Ruslan Salakhutdinov

ICML 2023 Grounding Language Models to Images for Multimodal Inputs and Outputs Jing Yu Koh, Ruslan Salakhutdinov, Daniel Fried

CoRL 2023 Imitating Task and Motion Planning with Visuomotor Transformers Murtaza Dalal, Ajay Mandlekar, Caelan Reed Garrett, Ankur Handa, Ruslan Salakhutdinov, Dieter Fox

NeurIPSW 2023 Mixture of Multimodal Interaction Experts Haofei Yu, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency

ICLR 2023 MultiViz: Towards Visualizing and Understanding Multimodal Models Paul Pu Liang, Yiwei Lyu, Gunjan Chhablani, Nihal Jain, Zihao Deng, Xingbo Wang, Louis-Philippe Morency, Ruslan Salakhutdinov

MLOSS 2023 MultiZoo and MultiBench: A Standardized Toolkit for Multimodal Deep Learning Paul Pu Liang, Yiwei Lyu, Xiang Fan, Arav Agarwal, Yun Cheng, Louis-Philippe Morency, Ruslan Salakhutdinov

NeurIPSW 2023 Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks Murtaza Dalal, Tarun Chiruvolu, Devendra Singh Chaplot, Ruslan Salakhutdinov

TMLR 2023 Probing Predictions on OOD Images via Nearest Categories Yao-Yuan Yang, Cyrus Rashtchian, Ruslan Salakhutdinov, Kamalika Chaudhuri

NeurIPS 2023 Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework Paul Pu Liang, Yun Cheng, Xiang Fan, Chun Kai Ling, Suzanne Nie, Richard Chen, Zihao Deng, Nicholas Allen, Randy Auerbach, Faisal Mahmood, Ruslan Salakhutdinov, Louis-Philippe Morency

NeurIPS 2023 SPRING: Studying Papers and Reasoning to Play Games Yue Wu, So Yeon Min, Shrimai Prabhumoye, Yonatan Bisk, Ruslan Salakhutdinov, Amos Azaria, Tom M. Mitchell, Yuanzhi Li

ICLR 2023 Scenario-Based Question Answering with Interacting Contextual Properties Haitian Sun, William W. Cohen, Ruslan Salakhutdinov

NeurIPSW 2023 Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data Chongyi Zheng, Benjamin Eysenbach, Homer Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine

NeurIPSW 2023 Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data Chongyi Zheng, Benjamin Eysenbach, Homer Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine

NeurIPSW 2022 A Connection Between One-Step Regularization and Critic Regularization in Reinforcement Learning Benjamin Eysenbach, Matthieu Geist, Ruslan Salakhutdinov, Sergey Levine

NeurIPSW 2022 A Connection Between One-Step Regularization and Critic Regularization in Reinforcement Learning Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov

ICLR 2022 C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez

ICLR 2022 Conditional Contrastive Learning with Kernel Yao-Hung Hubert Tsai, Tianqin Li, Martin Q. Ma, Han Zhao, Kun Zhang, Louis-Philippe Morency, Ruslan Salakhutdinov

NeurIPSW 2022 Contrastive Example-Based Control Kyle Beltran Hatch, Sarthak J Shetty, Benjamin Eysenbach, Tianhe Yu, Rafael Rafailov, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn

NeurIPSW 2022 Contrastive Example-Based Control Kyle Beltran Hatch, Sarthak J Shetty, Benjamin Eysenbach, Tianhe Yu, Rafael Rafailov, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn

NeurIPS 2022 Contrastive Learning as Goal-Conditioned Reinforcement Learning Benjamin Eysenbach, Tianjun Zhang, Sergey Levine, Ruslan Salakhutdinov

ICLR 2022 FILM: Following Instructions in Language with Modular Methods So Yeon Min, Devendra Singh Chaplot, Pradeep Kumar Ravikumar, Yonatan Bisk, Ruslan Salakhutdinov

ECML-PKDD 2022 Feature-Robust Optimal Transport for High-Dimensional Data Mathis Petrovich, Chao Liang, Ryoma Sato, Yanbin Liu, Yao-Hung Hubert Tsai, Linchao Zhu, Yi Yang, Ruslan Salakhutdinov, Makoto Yamada

NeurIPS 2022 Imitating past Successes Can Be Very Suboptimal Benjamin Eysenbach, Soumith Udatha, Ruslan Salakhutdinov, Sergey Levine

ICLR 2022 Learning Weakly-Supervised Contrastive Representations Yao-Hung Hubert Tsai, Tianqin Li, Weixin Liu, Peiyuan Liao, Ruslan Salakhutdinov, Louis-Philippe Morency

NeurIPS 2022 Mismatched No More: Joint Model-Policy Optimization for Model-Based RL Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov

ECCV 2022 PACS: A Dataset for Physical Audiovisual Commonsense Reasoning Samuel Yu, Peter Wu, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency

NeurIPS 2022 Paraphrasing Is All You Need for Novel Object Captioning Cheng-Fu Yang, Yao-Hung Hubert Tsai, Wan-Cyuan Fan, Ruslan Salakhutdinov, Louis-Philippe Morency, Frank Wang

ICML 2022 Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs Tianwei Ni, Benjamin Eysenbach, Ruslan Salakhutdinov

NeurIPSW 2022 Tackling AlfWorld with Action Attention and Common Sense from Language Models Yue Wu, So Yeon Min, Yonatan Bisk, Ruslan Salakhutdinov, Shrimai Prabhumoye

ICLR 2022 The Information Geometry of Unsupervised Reinforcement Learning Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine

NeurIPS 2022 Zero-Shot Transfer Learning Within a Heterogeneous Graph via Knowledge Transfer Networks Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi

NeurIPS 2021 Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives Murtaza Dalal, Deepak Pathak, Ruslan Salakhutdinov

NeurIPSW 2021 Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives Murtaza Dalal, Deepak Pathak, Ruslan Salakhutdinov

ICLR 2021 C-Learning: Learning to Achieve Goals via Recursive Classification Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine

NeurIPSW 2021 C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez

ICML 2021 Information Obfuscation of Graph Neural Networks Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov

ICML 2021 Instabilities of Offline RL with Pre-Trained Neural Representation Ruosong Wang, Yifan Wu, Ruslan Salakhutdinov, Sham Kakade

ECML-PKDD 2021 LSMI-Sinkhorn: Semi-Supervised Mutual Information Estimation with Optimal Transport Yanbin Liu, Makoto Yamada, Yao-Hung Hubert Tsai, Tam Le, Ruslan Salakhutdinov, Yi Yang

ICCV 2021 Learning to Hallucinate Examples from Extrinsic and Intrinsic Supervision Liangke Gui, Adrien Bardes, Ruslan Salakhutdinov, Alexander Hauptmann, Martial Hebert, Yu-Xiong Wang

NeurIPSW 2021 Mismatched No More: Joint Model-Policy Optimization for Model-Based RL Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov

ICLR 2021 Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers Benjamin Eysenbach, Shreyas Chaudhari, Swapnil Asawa, Sergey Levine, Ruslan Salakhutdinov

ICML 2021 On Proximal Policy Optimization’s Heavy-Tailed Gradients Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, Zico Kolter, Zachary Lipton, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Pradeep Ravikumar

ICML 2021 Reasoning over Virtual Knowledge Bases with Open Predicate Relations Haitian Sun, Patrick Verga, Bhuwan Dhingra, Ruslan Salakhutdinov, William W Cohen

NeurIPS 2021 Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification Ben Eysenbach, Sergey Levine, Ruslan Salakhutdinov

NeurIPS 2021 Robust Predictable Control Ben Eysenbach, Ruslan Salakhutdinov, Sergey Levine

NeurIPS 2021 SEAL: Self-Supervised Embodied Active Learning Using Exploration and 3D Consistency Devendra Singh Chaplot, Murtaza Dalal, Saurabh Gupta, Jitendra Malik, Ruslan Salakhutdinov

ICLR 2021 Self-Supervised Learning from a Multi-View Perspective Yao-Hung Hubert Tsai, Yue Wu, Ruslan Salakhutdinov, Louis-Philippe Morency

ICLR 2021 Self-Supervised Representation Learning with Relative Predictive Coding Yao-Hung Hubert Tsai, Martin Q. Ma, Muqiao Yang, Han Zhao, Louis-Philippe Morency, Ruslan Salakhutdinov

NeurIPSW 2021 The Information Geometry of Unsupervised Reinforcement Learning Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine

ICML 2021 Towards Understanding and Mitigating Social Biases in Language Models Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, Ruslan Salakhutdinov

ICML 2021 Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh

NeurIPS 2020 A Closer Look at Accuracy vs. Robustness Yao-Yuan Yang, Cyrus Rashtchian, Hongyang Zhang, Ruslan Salakhutdinov, Kamalika Chaudhuri

ICLR 2020 Capsules with Inverted Dot-Product Attention Routing Yao-Hung Hubert Tsai, Nitish Srivastava, Hanlin Goh, Ruslan Salakhutdinov

ICLR 2020 Differentiable Reasoning over a Virtual Knowledge Base Bhuwan Dhingra, Manzil Zaheer, Vidhisha Balachandran, Graham Neubig, Ruslan Salakhutdinov, William W. Cohen

IJCAI 2020 Embodied Multimodal Multitask Learning Devendra Singh Chaplot, Lisa Lee, Ruslan Salakhutdinov, Devi Parikh, Dhruv Batra

ICLR 2020 Harnessing the Power of Infinitely Wide Deep Nets on Small-Data Tasks Sanjeev Arora, Simon S. Du, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang, Dingli Yu

ICLR 2020 Learning to Explore Using Active Neural SLAM Devendra Singh Chaplot, Dhiraj Gandhi, Saurabh Gupta, Abhinav Gupta, Ruslan Salakhutdinov

NeurIPS 2020 Neural Methods for Point-Wise Dependency Estimation Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov

NeurIPS 2020 Object Goal Navigation Using Goal-Oriented Semantic Exploration Devendra Singh Chaplot, Dhiraj Prakashchand Gandhi, Abhinav Gupta, Ruslan Salakhutdinov

ICMLW 2020 Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers Benjamin Eysenbach, Swapnil Asawa, Shreyas Chaudhari, Ruslan Salakhutdinov, Sergey Levine

NeurIPS 2020 On Reward-Free Reinforcement Learning with Linear Function Approximation Ruosong Wang, Simon S Du, Lin Yang, Ruslan Salakhutdinov

NeurIPS 2020 Planning with General Objective Functions: Going Beyond Total Rewards Ruosong Wang, Peilin Zhong, Simon S Du, Ruslan Salakhutdinov, Lin Yang

NeurIPS 2020 Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension Ruosong Wang, Ruslan Salakhutdinov, Lin Yang

NeurIPS 2020 Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement Ben Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov

ICMLW 2020 Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement Benjamin Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov

NeurIPS 2020 Weakly-Supervised Reinforcement Learning for Controllable Behavior Lisa Lee, Ben Eysenbach, Ruslan Salakhutdinov, Shixiang Gu, Chelsea Finn

ICLR 2019 AutoLoss: Learning Discrete Schedule for Alternate Optimization Haowen Xu, Hao Zhang, Zhiting Hu, Xiaodan Liang, Ruslan Salakhutdinov, Eric Xing

ICLRW 2019 Connecting the Dots Between MLE and RL for Sequence Generation Bowen Tan, Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing

NeurIPS 2019 Deep Gamblers: Learning to Abstain with Portfolio Theory Ziyin Liu, Zhikang Wang, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency, Masahito Ueda

AISTATS 2019 Deep Neural Networks with Multi-Branch Architectures Are Intrinsically Less Non-Convex Hongyang Zhang, Junru Shao, Ruslan Salakhutdinov

NeurIPS 2019 Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels Simon S Du, Kangcheng Hou, Ruslan Salakhutdinov, Barnabas Poczos, Ruosong Wang, Keyulu Xu

NeurIPS 2019 Learning Data Manipulation for Augmentation and Weighting Zhiting Hu, Bowen Tan, Ruslan Salakhutdinov, Tom M. Mitchell, Eric P Xing

ICLR 2019 Learning Factorized Multimodal Representations Yao-Hung Hubert Tsai, Paul Pu Liang, Amir Zadeh, Louis-Philippe Morency, Ruslan Salakhutdinov

NeurIPS 2019 Learning Neural Networks with Adaptive Regularization Han Zhao, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov, Geoffrey J. Gordon

IJCAI 2019 MineRL: A Large-Scale Dataset of Minecraft Demonstrations William H. Guss, Brandon Houghton, Nicholay Topin, Phillip Wang, Cayden R. Codel, Manuela Veloso, Ruslan Salakhutdinov

NeurIPS 2019 Mixtape: Breaking the SoftMax Bottleneck Efficiently Zhilin Yang, Thang Luong, Ruslan Salakhutdinov, Quoc V Le

NeurIPS 2019 Multiple Futures Prediction Charlie Tang, Ruslan Salakhutdinov

NeurIPS 2019 On Exact Computation with an Infinitely Wide Neural Net Sanjeev Arora, Simon S Du, Wei Hu, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang

ICLRW 2019 Point Cloud GAN Chun-Liang Li, Manzil Zaheer, Yang Zhang, Barnabás Póczos, Ruslan Salakhutdinov

ICLR 2019 Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator Makoto Yamada, Denny Wu, Yao-Hung Hubert Tsai, Hirofumi Ohta, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu

AAAI 2019 Revisiting LSTM Networks for Semi-Supervised Text Classification via Mixed Objective Function Devendra Singh Sachan, Manzil Zaheer, Ruslan Salakhutdinov

NeurIPS 2019 Search on the Replay Buffer: Bridging Planning and Reinforcement Learning Ben Eysenbach, Ruslan Salakhutdinov, Sergey Levine

CoRL 2019 Worst Cases Policy Gradients Yichuan Charlie Tang, Jian Zhang, Ruslan Salakhutdinov

NeurIPS 2019 XLNet: Generalized Autoregressive Pretraining for Language Understanding Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, Quoc V Le

ICLR 2018 Neural mAP: Structured Memory for Deep Reinforcement Learning Emilio Parisotto, Ruslan Salakhutdinov

AISTATS 2018 A Generic Approach for Escaping Saddle Points Sashank J. Reddi, Manzil Zaheer, Suvrit Sra, Barnabás Póczos, Francis R. Bach, Ruslan Salakhutdinov, Alexander J. Smola

ICLR 2018 Active Neural Localization Devendra Singh Chaplot, Emilio Parisotto, Ruslan Salakhutdinov

ICLR 2018 Breaking the SoftMax Bottleneck: A High-Rank RNN Language Model Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov, William W. Cohen

NeurIPS 2018 Deep Generative Models with Learnable Knowledge Constraints Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Lianhui Qin, Xiaodan Liang, Haoye Dong, Eric P Xing

NeurIPS 2018 GLoMo: Unsupervised Learning of Transferable Relational Graphs Zhilin Yang, Jake Zhao, Bhuwan Dhingra, Kaiming He, William W. Cohen, Ruslan Salakhutdinov, Yann LeCun

ICML 2018 Gated Path Planning Networks Lisa Lee, Emilio Parisotto, Devendra Singh Chaplot, Eric Xing, Ruslan Salakhutdinov

AAAI 2018 Gated-Attention Architectures for Task-Oriented Language Grounding Devendra Singh Chaplot, Kanthashree Mysore Sathyendra, Rama Kumar Pasumarthi, Dheeraj Rajagopal, Ruslan Salakhutdinov

CVPRW 2018 Global Pose Estimation with an Attention-Based Recurrent Network Emilio Parisotto, Devendra Singh Chaplot, Jian Zhang, Ruslan Salakhutdinov

NeurIPS 2018 How Many Samples Are Needed to Estimate a Convolutional Neural Network? Simon S Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh

AAAI 2018 Knowledge-Based Word Sense Disambiguation Using Topic Models Devendra Singh Chaplot, Ruslan Salakhutdinov

ICLR 2018 On Unifying Deep Generative Models Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing

ICML 2018 Structured Control Nets for Deep Reinforcement Learning Mario Srouji, Jian Zhang, Ruslan Salakhutdinov

ICML 2018 Transformation Autoregressive Networks Junier Oliva, Avinava Dubey, Manzil Zaheer, Barnabas Poczos, Ruslan Salakhutdinov, Eric Xing, Jeff Schneider

ICCV 2017 Deep Determinantal Point Process for Large-Scale Multi-Label Classification Pengtao Xie, Ruslan Salakhutdinov, Luntian Mou, Eric P. Xing

NeurIPS 2017 Deep Sets Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Ruslan Salakhutdinov, Alexander J Smola

NeurIPS 2017 Good Semi-Supervised Learning That Requires a Bad GAN Zihang Dai, Zhilin Yang, Fan Yang, William W. Cohen, Ruslan Salakhutdinov

ICML 2017 Improved Variational Autoencoders for Text Modeling Using Dilated Convolutions Zichao Yang, Zhiting Hu, Ruslan Salakhutdinov, Taylor Berg-Kirkpatrick

ICCV 2017 Learning Robust Visual-Semantic Embeddings Yao-Hung Hubert Tsai, Liang-Kang Huang, Ruslan Salakhutdinov

ICLR 2017 On the Quantitative Analysis of Decoder-Based Generative Models Yuhuai Wu, Yuri Burda, Ruslan Salakhutdinov, Roger B. Grosse

CVPR 2017 Spatially Adaptive Computation Time for Residual Networks Michael Figurnov, Maxwell D. Collins, Yukun Zhu, Li Zhang, Jonathan Huang, Dmitry Vetrov, Ruslan Salakhutdinov

CVPR 2017 The More You Know: Using Knowledge Graphs for Image Classification Kenneth Marino, Ruslan Salakhutdinov, Abhinav Gupta

ICML 2017 Toward Controlled Generation of Text Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing

ICLR 2017 Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks Zhilin Yang, Ruslan Salakhutdinov, William W. Cohen

ICLR 2017 Words or Characters? Fine-Grained Gating for Reading Comprehension Zhilin Yang, Bhuwan Dhingra, Ye Yuan, Junjie Hu, William W. Cohen, Ruslan Salakhutdinov

ICLR 2016 Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning Emilio Parisotto, Lei Jimmy Ba, Ruslan Salakhutdinov

NeurIPS 2016 Architectural Complexity Measures of Recurrent Neural Networks Saizheng Zhang, Yuhuai Wu, Tong Che, Zhouhan Lin, Roland Memisevic, Ruslan Salakhutdinov, Yoshua Bengio

ICLR 2016 Data-Dependent Path Normalization in Neural Networks Behnam Neyshabur, Ryota Tomioka, Ruslan Salakhutdinov, Nathan Srebro

AISTATS 2016 Deep Kernel Learning Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing

ICLR 2016 Generating Images from Captions with Attention Elman Mansimov, Emilio Parisotto, Lei Jimmy Ba, Ruslan Salakhutdinov

ICLR 2016 Importance Weighted Autoencoders Yuri Burda, Roger B. Grosse, Ruslan Salakhutdinov

NeurIPS 2016 Iterative Refinement of the Approximate Posterior for Directed Belief Networks Devon Hjelm, Ruslan Salakhutdinov, Kyunghyun Cho, Nebojsa Jojic, Vince Calhoun, Junyoung Chung

NeurIPS 2016 On Multiplicative Integration with Recurrent Neural Networks Yuhuai Wu, Saizheng Zhang, Ying Zhang, Yoshua Bengio, Ruslan Salakhutdinov

NeurIPS 2016 Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations Behnam Neyshabur, Yuhuai Wu, Ruslan Salakhutdinov, Nati Srebro

NeurIPS 2016 Review Networks for Caption Generation Zhilin Yang, Ye Yuan, Yuexin Wu, William W. Cohen, Ruslan Salakhutdinov

NeurIPS 2016 Stochastic Variational Deep Kernel Learning Andrew G Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P Xing

AISTATS 2015 Accurate and Conservative Estimates of MRF Log-Likelihood Using Reverse Annealing Yuri Burda, Roger B. Grosse, Ruslan Salakhutdinov

ICCV 2015 Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books Yukun Zhu, Ryan Kiros, Rich Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, Sanja Fidler

NeurIPS 2015 Learning Wake-Sleep Recurrent Attention Models Jimmy Ba, Ruslan Salakhutdinov, Roger B Grosse, Brendan J. Frey

NeurIPS 2015 Path-SGD: Path-Normalized Optimization in Deep Neural Networks Behnam Neyshabur, Ruslan Salakhutdinov, Nati Srebro

ICCV 2015 Predicting Deep Zero-Shot Convolutional Neural Networks Using Textual Descriptions Jimmy Lei Ba, Kevin Swersky, Sanja Fidler, Ruslan Salakhutdinov

NeurIPS 2015 Skip-Thought Vectors Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov, Richard Zemel, Raquel Urtasun, Antonio Torralba, Sanja Fidler

CVPR 2015 segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection Yukun Zhu, Raquel Urtasun, Ruslan Salakhutdinov, Sanja Fidler

NeurIPS 2014 A Multiplicative Model for Learning Distributed Text-Based Attribute Representations Ryan Kiros, Richard Zemel, Ruslan Salakhutdinov

ICLR 2014 Deep Learning for Neuroimaging: A Validation Study Sergey M. Plis, R. Devon Hjelm, Ruslan Salakhutdinov, Vince D. Calhoun

JMLR 2014 Dropout: A Simple Way to Prevent Neural Networks from Overfitting Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, Ruslan Salakhutdinov

NeurIPS 2014 Learning Generative Models with Visual Attention Charlie Tang, Nitish Srivastava, Ruslan Salakhutdinov

JMLR 2014 Multimodal Learning with Deep Boltzmann Machines Nitish Srivastava, Ruslan Salakhutdinov

ICML 2014 Multimodal Neural Language Models Ryan Kiros, Ruslan Salakhutdinov, Rich Zemel

NeurIPS 2013 Annealing Between Distributions by Averaging Moments Roger B Grosse, Chris J Maddison, Ruslan Salakhutdinov

NeurIPS 2013 Discriminative Transfer Learning with Tree-Based Priors Nitish Srivastava, Ruslan Salakhutdinov

NeurIPS 2013 Learning Stochastic Feedforward Neural Networks Charlie Tang, Ruslan Salakhutdinov

UAI 2013 Modeling Documents with Deep Boltzmann Machines Nitish Srivastava, Ruslan Salakhutdinov, Geoffrey E. Hinton

NeurIPS 2013 One-Shot Learning by Inverting a Compositional Causal Process Brenden M Lake, Ruslan Salakhutdinov, Josh Tenenbaum

ICML 2013 Tensor Analyzers Yichuan Tang, Ruslan Salakhutdinov, Geoffrey Hinton

NeurIPS 2013 The Power of Asymmetry in Binary Hashing Behnam Neyshabur, Nati Srebro, Ruslan Salakhutdinov, Yury Makarychev, Payman Yadollahpour

NeurIPS 2012 A Better Way to Pretrain Deep Boltzmann Machines Geoffrey E. Hinton, Ruslan Salakhutdinov

NeurIPS 2012 Cardinality Restricted Boltzmann Machines Kevin Swersky, Ilya Sutskever, Daniel Tarlow, Richard S. Zemel, Ruslan Salakhutdinov, Ryan P. Adams

ICML 2012 Deep Lambertian Networks Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton

ICML 2012 Deep Mixtures of Factor Analysers Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton

AISTATS 2012 Domain Adaptation: A Small Sample Statistical Approach Ruslan Salakhutdinov, Sham Kakade, Dean Foster

UAI 2012 Exploiting Compositionality to Explore a Large Space of Model Structures Roger B. Grosse, Ruslan Salakhutdinov, William T. Freeman, Joshua B. Tenenbaum

NeurIPS 2012 Hamming Distance Metric Learning Mohammad Norouzi, David J Fleet, Ruslan Salakhutdinov

NeurIPS 2012 Matrix Reconstruction with the Local Max Norm Rina Foygel, Nathan Srebro, Ruslan Salakhutdinov

NeurIPS 2012 Multimodal Learning with Deep Boltzmann Machines Nitish Srivastava, Ruslan Salakhutdinov

CVPR 2012 Robust Boltzmann Machines for Recognition and Denoising Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton

NeurIPS 2011 Learning to Learn with Compound HD Models Antonio Torralba, Joshua B. Tenenbaum, Ruslan Salakhutdinov

CVPR 2011 Learning to Share Visual Appearance for Multiclass Object Detection Ruslan Salakhutdinov, Antonio Torralba, Joshua B. Tenenbaum

NeurIPS 2011 Learning with the Weighted Trace-Norm Under Arbitrary Sampling Distributions Rina Foygel, Ohad Shamir, Nati Srebro, Ruslan Salakhutdinov

NeurIPS 2011 Transfer Learning by Borrowing Examples for Multiclass Object Detection Joseph J. Lim, Ruslan Salakhutdinov, Antonio Torralba

NeurIPS 2010 Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm Nathan Srebro, Ruslan Salakhutdinov

AISTATS 2010 Efficient Learning of Deep Boltzmann Machines Ruslan Salakhutdinov, Hugo Larochelle

ICML 2010 Learning Deep Boltzmann Machines Using Adaptive MCMC Ruslan Salakhutdinov

NeurIPS 2010 Practical Large-Scale Optimization for Max-Norm Regularization Jason Lee, Ben Recht, Nathan Srebro, Joel Tropp, Ruslan Salakhutdinov

AISTATS 2009 Deep Boltzmann Machines Ruslan Salakhutdinov, Geoffrey Hinton

ICML 2009 Evaluation Methods for Topic Models Hanna M. Wallach, Iain Murray, Ruslan Salakhutdinov, David M. Mimno

ICML 2009 Learning Nonlinear Dynamic Models John Langford, Ruslan Salakhutdinov, Tong Zhang

NeurIPS 2009 Learning in Markov Random Fields Using Tempered Transitions Ruslan Salakhutdinov

NeurIPS 2009 Modelling Relational Data Using Bayesian Clustered Tensor Factorization Ilya Sutskever, Joshua B. Tenenbaum, Ruslan Salakhutdinov

NeurIPS 2009 Replicated SoftMax: An Undirected Topic Model Geoffrey E. Hinton, Ruslan Salakhutdinov

ICML 2009 Workshop Summary: Workshop on Learning Feature Hierarchies Kai Yu, Ruslan Salakhutdinov, Yann LeCun, Geoffrey E. Hinton, Yoshua Bengio

ICML 2008 Bayesian Probabilistic Matrix Factorization Using Markov Chain Monte Carlo Ruslan Salakhutdinov, Andriy Mnih

NeurIPS 2008 Evaluating Probabilities Under High-Dimensional Latent Variable Models Iain Murray, Ruslan Salakhutdinov

ICML 2008 On the Quantitative Analysis of Deep Belief Networks Ruslan Salakhutdinov, Iain Murray

AISTATS 2007 Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure Ruslan Salakhutdinov, Geoff Hinton

NeurIPS 2007 Probabilistic Matrix Factorization Andriy Mnih, Ruslan Salakhutdinov

ICML 2007 Restricted Boltzmann Machines for Collaborative Filtering Ruslan Salakhutdinov, Andriy Mnih, Geoffrey E. Hinton

NeurIPS 2007 Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes Geoffrey E. Hinton, Ruslan Salakhutdinov

NeurIPS 2004 Neighbourhood Components Analysis Jacob Goldberger, Geoffrey E. Hinton, Sam T. Roweis, Ruslan Salakhutdinov

ICML 2003 Adaptive Overrelaxed Bound Optimization Methods Ruslan Salakhutdinov, Sam T. Roweis

UAI 2003 On the Convergence of Bound Optimization Algorithms Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani

ICML 2003 Optimization with EM and Expectation-Conjugate-Gradient Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani