Venkatesh, Svetha

124 publications

WACV 2025 Fair Domain Generalization with Heterogeneous Sensitive Attributes Across Domains Ragja Palakkadavath, Hung Le, Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh

AAAI 2025 Multi-Reference Preference Optimization for Large Language Models Hung Le, Quan Hung Tran, Dung Nguyen, Kien Do, Saloni Mittal, Kelechi Ogueji, Svetha Venkatesh

IJCAI 2025 Navigating Social Dilemmas with LLM-Based Agents via Consideration of Future Consequences Dung Nguyen, Hung Le, Kien Do, Sunil Gupta, Svetha Venkatesh, Truyen Tran

TMLR 2025 Reasoning Under 1 Billion: Memory-Augmented Reinforcement Learning for Large Language Models Hung Le, Van Dai Do, Dung Nguyen, Svetha Venkatesh

NeurIPS 2025 Reproducing Kernel Banach Space Models for Neural Networks with Application to Rademacher Complexity Analysis Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh

ICLR 2025 Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning Hung Le, Dung Nguyen, Kien Do, Sunil Gupta, Svetha Venkatesh

NeurIPS 2024 Active Set Ordering Quoc Phong Nguyen, Sunil Gupta, Svetha Venkatesh, Bryan Kian Hsiang Low, Patrick Jaillet

IJCAI 2024 Diversifying Training Pool Predictability for Zero-Shot Coordination: A Theory of Mind Approach Dung Nguyen, Hung Le, Kien Do, Sunil Gupta, Svetha Venkatesh, Truyen Tran

ECML-PKDD 2024 Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties A. V. Arun Kumar, Alistair Shilton, Sunil Gupta, Santu Rana, Stewart Greenhill, Svetha Venkatesh

WACV 2024 Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection Tuan Hoang, Santu Rana, Sunil Gupta, Svetha Venkatesh

TMLR 2024 Plug, Play, and Generalize: Length Extrapolation with Pointer-Augmented Neural Memory Hung Le, Dung Nguyen, Kien Do, Svetha Venkatesh, Truyen Tran

AAAI 2024 Root Cause Explanation of Outliers Under Noisy Mechanisms Phuoc Nguyen, Truyen Tran, Sunil Gupta, Thin Nguyen, Svetha Venkatesh

ECML-PKDD 2024 Variable-Agnostic Causal Exploration for Reinforcement Learning Minh Hoang Nguyen, Hung Le, Svetha Venkatesh

ACML 2023 Domain Generalization with Interpolation Robustness Ragja Palakkadavath, Thanh Nguyen-Tang, Hung Le, Svetha Venkatesh, Sunil Gupta

ICML 2023 Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh

WACV 2023 Guiding Visual Question Answering with Attention Priors Thao Minh Le, Vuong Le, Sunil Gupta, Svetha Venkatesh, Truyen Tran

NeurIPSW 2023 Hierarchical GFlowNet for Crystal Structure Generation Tri Minh Nguyen, Sherif Abdulkader Tawfik, Truyen Tran, Sunil Gupta, Santu Rana, Svetha Venkatesh

AAAI 2023 Memory-Augmented Theory of Mind Network Dung Nguyen, Phuoc Nguyen, Hung Le, Kien Do, Svetha Venkatesh, Truyen Tran

ICCV 2023 Multi-Weather Image Restoration via Domain Translation Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh, Subrahmanyam Murala

AAAI 2023 On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora

ICCV 2023 Persistent-Transient Duality: A Multi-Mechanism Approach for Modeling Human-Object Interaction Hung Tran, Vuong Le, Svetha Venkatesh, Truyen Tran

IJCAI 2023 Social Motivation for Modelling Other Agents Under Partial Observability in Decentralised Training Dung Nguyen, Hung Le, Kien Do, Svetha Venkatesh, Truyen Tran

AISTATS 2022 Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh

ECCV 2022 Black-Box Few-Shot Knowledge Distillation Dang Nguyen, Sunil Gupta, Kien Do, Svetha Venkatesh

AAAI 2022 Episodic Policy Gradient Training Hung Le, Majid Abdolshah, Thommen George Karimpanal, Kien Do, Dung Nguyen, Svetha Venkatesh

NeurIPS 2022 Expected Improvement for Contextual Bandits Hung Tran-The, Sunil Gupta, Santu Rana, Tuan Truong, Long Tran-Thanh, Svetha Venkatesh

ICLR 2022 Generative Pseudo-Inverse Memory Kha Pham, Hung Le, Man Ngo, Truyen Tran, Bao Ho, Svetha Venkatesh

NeurIPS 2022 Human-AI Collaborative Bayesian Optimisation A V Arun Kumar, Santu Rana, Alistair Shilton, Svetha Venkatesh

NeurIPSW 2022 Improving Domain Generalization with Interpolation Robustness Ragja Palakkadavath, Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh

NeurIPSW 2022 Improving Domain Generalization with Interpolation Robustness Ragja Palakkadavath, Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh

NeurIPS 2022 Learning to Constrain Policy Optimization with Virtual Trust Region Thai Hung Le, Thommen Karimpanal George, Majid Abdolshah, Dung Nguyen, Kien Do, Sunil Gupta, Svetha Venkatesh

NeurIPS 2022 Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation Kien Do, Thai Hung Le, Dung Nguyen, Dang Nguyen, Haripriya Harikumar, Truyen Tran, Santu Rana, Svetha Venkatesh

ICML 2022 Neurocoder: General-Purpose Computation Using Stored Neural Programs Hung Le, Svetha Venkatesh

ICLR 2022 Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization Thanh Nguyen-Tang, Sunil Gupta, A. Tuan Nguyen, Svetha Venkatesh

TMLR 2022 On Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks in Besov Spaces Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh

CVPRW 2022 Persistent-Transient Duality in Human Behavior Modeling Hung Tran, Vuong Le, Svetha Venkatesh, Truyen Tran

AAAI 2022 TRF: Learning Kernels with Tuned Random Features Alistair Shilton, Sunil Gupta, Santu Rana, Arun Kumar Anjanapura Venkatesh, Svetha Venkatesh

ECCV 2022 Towards Effective and Robust Neural Trojan Defenses via Input Filtering Kien Do, Haripriya Harikumar, Hung Le, Dung Nguyen, Truyen Tran, Santu Rana, Dang Nguyen, Willy Susilo, Svetha Venkatesh

ECCV 2022 Video Restoration Framework and Its Meta-Adaptations to Data-Poor Conditions Prashant W Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh

ICML 2021 A New Representation of Successor Features for Transfer Across Dissimilar Environments Majid Abdolshah, Hung Le, Thommen Karimpanal George, Sunil Gupta, Santu Rana, Svetha Venkatesh

ICML 2021 Bayesian Optimistic Optimisation with Exponentially Decaying Regret Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh

ICCV 2021 Clustering by Maximizing Mutual Information Across Views Kien Do, Truyen Tran, Svetha Venkatesh

AAAI 2021 Distributional Reinforcement Learning via Moment Matching Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh

ECML-PKDD 2021 Fast Conditional Network Compression Using Bayesian HyperNetworks Phuoc Nguyen, Truyen Tran, Ky Le, Sunil Gupta, Santu Rana, Dang Nguyen, Trong Nguyen, Shannon Ryan, Svetha Venkatesh

AAAI 2021 High Dimensional Level Set Estimation with Bayesian Neural Network Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh

NeurIPS 2021 Kernel Functional Optimisation Arun Kumar Anjanapura Venkatesh, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

ECML-PKDD 2021 Knowledge Distillation with Distribution Mismatch Dang Nguyen, Sunil Gupta, Trong Nguyen, Santu Rana, Phuoc Nguyen, Truyen Tran, Ky Le, Shannon Ryan, Svetha Venkatesh

CVPR 2021 Learning Asynchronous and Sparse Human-Object Interaction in Videos Romero Morais, Vuong Le, Svetha Venkatesh, Truyen Tran

NeurIPS 2021 Model-Based Episodic Memory Induces Dynamic Hybrid Controls Hung Le, Thommen Karimpanal George, Majid Abdolshah, Truyen Tran, Svetha Venkatesh

AAAI 2021 Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization Kien Do, Truyen Tran, Svetha Venkatesh

ECML-PKDD 2021 Variational Hyper-Encoding Networks Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Hieu-Chi Dam, Svetha Venkatesh

AISTATS 2020 Accelerated Bayesian Optimisation Through Weight-Prior Tuning Alistair Shilton, Sunil Gupta, Santu Rana, Pratibha Vellanki, Cheng Li, Svetha Venkatesh, Laurence Park, Alessandra Sutti, David Rubin, Thomas Dorin, Alireza Vahid, Murray Height, Teo Slezak

AAAI 2020 Bayesian Optimization for Categorical and Category-Specific Continuous Inputs Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh

ECML-PKDD 2020 Bayesian Optimization with Missing Inputs Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh

ICML 2020 DeepCoDA: Personalized Interpretability for Compositional Health Data Thomas Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh

AISTATS 2020 Distributionally Robust Bayesian Quadrature Optimization Thanh Nguyen, Sunil Gupta, Huong Ha, Santu Rana, Svetha Venkatesh

IJCAI 2020 Dynamic Language Binding in Relational Visual Reasoning Thao Minh Le, Vuong Le, Svetha Venkatesh, Truyen Tran

ICLR 2020 Neural Stored-Program Memory Hung Le, Truyen Tran, Svetha Venkatesh

IJCAI 2020 Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh

ECML-PKDD 2020 Scalable Backdoor Detection in Neural Networks Haripriya Harikumar, Vuong Le, Santu Rana, Sourangshu Bhattacharya, Sunil Gupta, Svetha Venkatesh

ICML 2020 Self-Attentive Associative Memory Hung Le, Truyen Tran, Svetha Venkatesh

NeurIPS 2020 Sub-Linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces Hung Tran-The, Sunil Gupta, Santu Rana, Huong Ha, Svetha Venkatesh

ACML 2020 Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning Dung Nguyen, Svetha Venkatesh, Phuoc Nguyen, Truyen Tran

AAAI 2020 Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh

MLJ 2019 Attentional Multilabel Learning over Graphs: A Message Passing Approach Kien Do, Truyen Tran, Thin Nguyen, Svetha Venkatesh

AAAI 2019 Bayesian Functional Optimisation with Shape Prior Pratibha Vellanki, Santu Rana, Sunil Gupta, David Rubin de Celis Leal, Alessandra Sutti, Murray Height, Svetha Venkatesh

NeurIPS 2019 Bayesian Optimization with Unknown Search Space Huong Ha, Santu Rana, Sunil Gupta, Thanh Nguyen, Hung Tran-The, Svetha Venkatesh

ICLR 2019 Improving Generalization and Stability of Generative Adversarial Networks Hoang Thanh-Tung, Truyen Tran, Svetha Venkatesh

ICLR 2019 Learning to Remember More with Less Memorization Hung Le, Truyen Tran, Svetha Venkatesh

NeurIPS 2019 Multi-Objective Bayesian Optimisation with Preferences over Objectives Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

NeurIPS 2018 Algorithmic Assurance: An Active Approach to Algorithmic Testing Using Bayesian Optimisation Shivapratap Gopakumar, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh

AISTATS 2018 Exploiting Strategy-Space Diversity for Batch Bayesian Optimization Sunil Gupta, Alistair Shilton, Santu Rana, Svetha Venkatesh

ECML-PKDD 2018 Exploration Enhanced Expected Improvement for Bayesian Optimization Julian Berk, Vu Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh

ECML-PKDD 2018 Information-Theoretic Transfer Learning Framework for Bayesian Optimisation Anil Ramachandran, Sunil Gupta, Santu Rana, Svetha Venkatesh

UAI 2018 Multi-Target Optimisation via Bayesian Optimisation and Linear Programming Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

ECML-PKDD 2018 Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Q. Phung

NeurIPS 2018 Variational Memory Encoder-Decoder Hung Le, Truyen Tran, Thin Nguyen, Svetha Venkatesh

AAAI 2017 Column Networks for Collective Classification Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh

IJCAI 2017 High Dimensional Bayesian Optimization Using Dropout Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Alistair Shilton

ICML 2017 High Dimensional Bayesian Optimization with Elastic Gaussian Process Santu Rana, Cheng Li, Sunil Gupta, Vu Nguyen, Svetha Venkatesh

NeurIPS 2017 Process-Constrained Batch Bayesian Optimisation Pratibha Vellanki, Santu Rana, Sunil Gupta, David Rubin, Alessandra Sutti, Thomas Dorin, Murray Height, Paul Sanders, Svetha Venkatesh

AISTATS 2017 Regret Bounds for Transfer Learning in Bayesian Optimisation Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh

ACML 2017 Regret for Expected Improvement over the Best-Observed Value and Stopping Condition Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh

ACML 2016 A Bayesian Nonparametric Approach for Multi-Label Classification Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh

MLHC 2016 Preterm Birth Prediction: Stable Selection of Interpretable Rules from High Dimensional Data Truyen Tran, Wei Luo, Dinh Phung, Jonathan Morris, Kristen Rickard, Svetha Venkatesh

UAI 2016 Scalable Nonparametric Bayesian Multilevel Clustering Viet Huynh, Dinh Q. Phung, Svetha Venkatesh, XuanLong Nguyen, Matthew D. Hoffman, Hung Hai Bui

IJCAI 2015 Groupwise Registration of Aerial Images Ognjen Arandjelovic, Duc-Son Pham, Svetha Venkatesh

ACML 2015 Streaming Variational Inference for Dirichlet Process Mixtures Viet Huynh, Dinh Phung, Svetha Venkatesh

AAAI 2015 Tensor-Variate Restricted Boltzmann Machines Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh

WACV 2015 Visual Object Clustering via Mixed-Norm Regularization Xin Zhang, Duc-Son Pham, Dinh Q. Phung, Wanquan Liu, Budhaditya Saha, Svetha Venkatesh

ICML 2013 Factorial Multi-Task Learning : A Bayesian Nonparametric Approach Sunil Gupta, Dinh Phung, Svetha Venkatesh

ACML 2013 Learning Parts-Based Representations with Nonnegative Restricted Boltzmann Machine Tu Dinh Nguyen, Truyen Tran, Dinh Phung, Svetha Venkatesh

ICML 2013 Thurstonian Boltzmann Machines: Learning from Multiple Inequalities Truyen Tran, Dinh Phung, Svetha Venkatesh

AAAI 2012 A Sequential Decision Approach to Ordinal Preferences in Recommender Systems Truyen Tran, Dinh Q. Phung, Svetha Venkatesh

UAI 2012 A Slice Sampler for Restricted Hierarchical Beta Process with Applications to Shared Subspace Learning Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh

ACML 2012 Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis Truyen Tran, Dinh Phung, Svetha Venkatesh

CVPR 2012 Improved Subspace Clustering via Exploitation of Spatial Constraints Duc-Son Pham, Budhaditya Saha, Dinh Q. Phung, Svetha Venkatesh

ACML 2012 Learning from Ordered Sets and Applications in Collaborative Ranking Truyen Tran, Dinh Phung, Svetha Venkatesh

CVPR 2011 Efficient Subwindow Search with Submodular Score Functions Senjian An, Patrick Peursum, Wanquan Liu, Svetha Venkatesh

ACML 2011 Mixed-Variate Restricted Boltzmann Machines Truyen Tran, Dinh Phung, Svetha Venkatesh

CVPR 2010 Exploiting Monge Structures in Optimum Subwindow Search Senjian An, Patrick Peursum, Wanquan Liu, Svetha Venkatesh, Xiaoming Chen

CVPR 2009 Efficient Algorithms for Subwindow Search in Object Detection and Localization Senjian An, Patrick Peursum, Wanquan Liu, Svetha Venkatesh

UAI 2009 Ordinal Boltzmann Machines for Collaborative Filtering Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh

CVPR 2008 Exploiting Side Information in Locality Preserving Projection Senjian An, Wanquan Liu, Svetha Venkatesh

NeurIPS 2008 Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data Tran T. Truyen, Dinh Phung, Hung Bui, Svetha Venkatesh

CVPR 2008 Joint Learning and Dictionary Construction for Pattern Recognition Duc-Son Pham, Svetha Venkatesh

CVPR 2008 Recognising Faces in Unseen Modes: A Tensor Based Approach Santu Rana, Wanquan Liu, Mihai M. Lazarescu, Svetha Venkatesh

CVPR 2008 Robust Learning of Discriminative Projection for Multicategory Classification on the Stiefel Manifold Duc-Son Pham, Svetha Venkatesh

AAAI 2008 The Hidden Permutation Model and Location-Based Activity Recognition Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh, Hai Phan

CVPR 2007 Face Recognition Using Kernel Ridge Regression Senjian An, Wanquan Liu, Svetha Venkatesh

IJCAI 2007 Face Recognition via the Overlapping Energy Histogram Ronny Tjahyadi, Wanquan Liu, Senjian An, Svetha Venkatesh

CVPR 2007 Tracking-as-Recognition for Articulated Full-Body Human Motion Analysis Patrick Peursum, Svetha Venkatesh, Geoff A. W. West

CVPR 2006 AdaBoost.MRF: Boosted Markov Random Forests and Application to Multilevel Activity Recognition Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui

CVPR 2005 Activity Recognition and Abnormality Detection with the Switching Hidden Semi-Markov Model Thi V. Duong, Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh

ICCV 2005 Combining Image Regions and Human Activity for Indirect Object Recognition in Indoor Wide-Angle Views Patrick Peursum, Geoff A. W. West, Svetha Venkatesh

CVPR 2005 Learning and Detecting Activities from Movement Trajectories Using the Hierarchical Hidden Markov Models Nam Thanh Nguyen, Dinh Q. Phung, Svetha Venkatesh, Hung Bui

AAAI 2004 Learning Hierarchical Hidden Markov Models with General State Hierarchy Hung Hai Bui, Dinh Q. Phung, Svetha Venkatesh

CVPR 2003 Recognising and Monitoring High-Level Behaviours in Complex Spatial Environments Nam Thanh Nguyen, Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West

JAIR 2002 Policy Recognition in the Abstract Hidden Markov Model Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West

AAAI 2000 On the Recognition of Abstract Markov Policies Hung Hai Bui, Svetha Venkatesh, Geoff A. W. West

CVPR 1999 Low-Cost Interactive Active Monocular Range Finder Masahiro Takatsuka, Geoff A. W. West, Svetha Venkatesh, Terry Caelli

AAAI 1996 Learning Other Agents' Preferences in Multiagent Negotiation Hung Hai Bui, Dorota H. Kieronska, Svetha Venkatesh

CVPR 1994 Emerging Hypothesis Verification Using Function-Based Geometric Models and Active Vision Strategies Chiou Peng Lam, Geoff A. W. West, Svetha Venkatesh

CVPR 1991 Early Jump-Out Corner Detectors James W. Cooper, Svetha Venkatesh, Leslie J. Kitchen