← Authors

Svetha Venkatesh

77 papers · 2008–2025 · 13 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (11) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (17) 🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (13) πŸ—ΊοΈ Taxonomy Completionist (26) 🀝 Dynamic Duo (43) πŸ‘‘ Triple Crown πŸ† Keyword Champion πŸ† Grand Slam 🌱 Topic Pioneer πŸ”¬ Deep Specialist (24) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (11) πŸ—ƒοΈ Keyword Collector (73) πŸ’Ž Century Club (77) ⚑ Prolific Year (9)

Conferences

NIPS (14) AAAI (12) ACML (9) ICML (9) IJCAI (7) ICLR (6) AISTATS (5) ICCV (4) CVPR (3) ECCV (3) WACV (3) ACL (1) MLHC (1)

Top co-authors

Sunil Gupta (43) Santu Rana (32) Truyen Tran (29) Hung Le (19) Kien Do (13) Dung Nguyen (11) Alistair Shilton (10) Dinh Phung (9) Vuong Le (7) Hung Tran-The (6)

Research topics

Computer Vision (1)

Keywords

bayesian optimization (19) gaussian process (13) regret bound (13) acquisition function (8) hyperparameter tuning (6) transfer learning (5) reinforcement learning (4) neural network (4) episodic memory (4) bayesian optimisation (4) representation learning (3) unsupervised learning (3) restricted boltzmann machine (3) relational reasoning (3) active learning (3) hyperparameter optimization (3) variational inference (3) expected improvement (3) visual question answering (3) black-box optimization (3)

Papers

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