Svetha Venkatesh

Dynamic Steering With Episodic Memory For Large Language Models ACL 2025 Fair Domain Generalization with Heterogeneous Sensitive Attributes Across Domains WACV 2025 Multi-Reference Preference Optimization for Large Language Models AAAI 2025 Navigating Social Dilemmas with LLM-based Agents via Consideration of Future Consequences IJCAI 2025 Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning ICLR 2025 Active Set Ordering NeurIPS 2024 Diversifying Training Pool Predictability for Zero-shot Coordination: A Theory of Mind Approach IJCAI 2024 Learn To Unlearn for Deep Neural Networks: Minimizing Unlearning Interference With Gradient Projection WACV 2024 Root Cause Explanation of Outliers under Noisy Mechanisms AAAI 2024 Domain Generalization with Interpolation Robustness ACML 2023 Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space ICML 2023 Guiding Visual Question Answering With Attention Priors WACV 2023 Memory-Augmented Theory of Mind Network AAAI 2023 Multi-weather Image Restoration via Domain Translation ICCV 2023 On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation AAAI 2023 Persistent-Transient Duality: A Multi-Mechanism Approach for Modeling Human-Object Interaction ICCV 2023 Social Motivation for Modelling Other Agents under Partial Observability in Decentralised Training IJCAI 2023 Black-Box Few-Shot Knowledge Distillation ECCV 2022 Episodic Policy Gradient Training AAAI 2022 Expected Improvement for Contextual Bandits NeurIPS 2022 Generative Pseudo-Inverse Memory ICLR 2022 Human-AI Collaborative Bayesian Optimisation NeurIPS 2022 Learning to Constrain Policy Optimization with Virtual Trust Region NeurIPS 2022 Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation NeurIPS 2022 Neurocoder: General-Purpose Computation Using Stored Neural Programs ICML 2022 Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization ICLR 2022 Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization AISTATS 2022 Towards Effective and Robust Neural Trojan Defenses via Input Filtering ECCV 2022 TRF: Learning Kernels with Tuned Random Features AAAI 2022 Video Restoration Framework and Its Meta-Adaptations to Data-Poor Conditions ECCV 2022 A New Representation of Successor Features for Transfer across Dissimilar Environments ICML 2021 Bayesian Optimistic Optimisation with Exponentially Decaying Regret ICML 2021 Clustering by Maximizing Mutual Information Across Views ICCV 2021 Distributional Reinforcement Learning via Moment Matching AAAI 2021 High Dimensional Level Set Estimation with Bayesian Neural Network AAAI 2021 Kernel Functional Optimisation NeurIPS 2021 Learning Asynchronous and Sparse Human-Object Interaction in Videos CVPR 2021 Model-Based Episodic Memory Induces Dynamic Hybrid Controls NeurIPS 2021 Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization AAAI 2021 Accelerated Bayesian Optimisation through Weight-Prior Tuning AISTATS 2020 Bayesian Optimization for Categorical and Category-Specific Continuous Inputs AAAI 2020 DeepCoDA: personalized interpretability for compositional health data ICML 2020 Distributionally Robust Bayesian Quadrature Optimization AISTATS 2020 Dynamic Language Binding in Relational Visual Reasoning IJCAI 2020 Hierarchical Conditional Relation Networks for Video Question Answering CVPR 2020 Neural Stored-program Memory ICLR 2020 Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation IJCAI 2020 Self-Attentive Associative Memory ICML 2020 Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces NeurIPS 2020 Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning ACML 2020 Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization AAAI 2020 Bayesian Functional Optimisation with Shape Prior AAAI 2019 Bayesian Optimization with Unknown Search Space NeurIPS 2019 Improving Generalization and Stability of Generative Adversarial Networks ICLR 2019 Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos CVPR 2019 Learning to Remember More with Less Memorization ICLR 2019 Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection ICCV 2019 Multi-objective Bayesian optimisation with preferences over objectives NeurIPS 2019 Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation NeurIPS 2018 Exploiting Strategy-Space Diversity for Batch Bayesian Optimization AISTATS 2018 Variational Memory Encoder-Decoder NeurIPS 2018 High Dimensional Bayesian Optimization using Dropout IJCAI 2017 High Dimensional Bayesian Optimization with Elastic Gaussian Process ICML 2017 Process-constrained batch Bayesian optimisation NeurIPS 2017 Regret Bounds for Transfer Learning in Bayesian Optimisation AISTATS 2017 Regret for Expected Improvement over the Best-Observed Value and Stopping Condition ACML 2017 A Bayesian Nonparametric Approach for Multi-label Classification ACML 2016 Preterm Birth Prediction: Stable Selection of Interpretable Rules from High Dimensional Data MLHC 2016 Groupwise Registration of Aerial Images IJCAI 2015 Streaming Variational Inference for Dirichlet Process Mixtures ACML 2015 Factorial Multi-Task Learning : A Bayesian Nonparametric Approach ICML 2013 Learning Parts-based Representations with Nonnegative Restricted Boltzmann Machine ACML 2013 Thurstonian Boltzmann Machines: Learning from Multiple Inequalities ICML 2013 Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis ACML 2012 Learning From Ordered Sets and Applications in Collaborative Ranking ACML 2012 Mixed-Variate Restricted Boltzmann Machines ACML 2011 Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data NeurIPS 2008