Kandasamy, Kirthevasan

32 publications

NeurIPS 2025 A Cramér–von Mises Approach to Incentivizing Truthful Data Sharing Alex Clinton, Thomas Zeng, Yiding Chen, Jerry Zhu, Kirthevasan Kandasamy

NeurIPS 2025 Balancing Performance and Costs in Best Arm Identification Michael O Harding, Kirthevasan Kandasamy

ICML 2025 Collaborative Mean Estimation Among Heterogeneous Strategic Agents: Individual Rationality, Fairness, and Truthful Contribution Alex Clinton, Yiding Chen, Jerry Zhu, Kirthevasan Kandasamy

NeurIPS 2024 Learning to Price Homogeneous Data Keran Chen, Joon Suk Huh, Kirthevasan Kandasamy

ICML 2024 Nash Incentive-Compatible Online Mechanism Learning via Weakly Differentially Private Online Learning Joon Suk Huh, Kirthevasan Kandasamy

AISTATS 2023 Active Cost-Aware Labeling of Streaming Data Ting Cai, Kirthevasan Kandasamy

NeurIPS 2023 Mechanism Design for Collaborative Normal Mean Estimation Yiding Chen, Xiaojin Zhu, Kirthevasan Kandasamy

JMLR 2023 VCG Mechanism Design with Unknown Agent Values Under Stochastic Bandit Feedback Kirthevasan Kandasamy, Joseph E Gonzalez, Michael I Jordan, Ion Stoica

AISTATS 2022 Learning Competitive Equilibria in Exchange Economies with Bandit Feedback Wenshuo Guo, Kirthevasan Kandasamy, Joseph Gonzalez, Michael Jordan, Ion Stoica

ICML 2021 Resource Allocation in Multi-Armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael Jordan, Ken Goldberg, Joseph Gonzalez

AISTATS 2020 ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy, Willie Neiswanger, Barnabas Poczos, Jeff Schneider, Eric Xing

JMLR 2020 Tuning Hyperparameters Without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria, Christopher R. Collins, Jeff Schneider, Barnabas Poczos, Eric P. Xing

UAI 2019 A Flexible Framework for Multi-Objective Bayesian Optimization Using Random Scalarizations Biswajit Paria, Kirthevasan Kandasamy, Barnabás Póczos

JAIR 2019 Multi-Fidelity Gaussian Process Bandit Optimisation Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos

ICML 2019 Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments Kirthevasan Kandasamy, Willie Neiswanger, Reed Zhang, Akshay Krishnamurthy, Jeff Schneider, Barnabas Poczos

AISTATS 2019 Noisy Blackbox Optimization Using Multi-Fidelity Queries: A Tree Search Approach Rajat Sen, Kirthevasan Kandasamy, Sanjay Shakkottai

NeurIPS 2019 Offline Contextual Bayesian Optimization Ian Char, Youngseog Chung, Willie Neiswanger, Kirthevasan Kandasamy, Andrew Oakleigh Nelson, Mark Boyer, Egemen Kolemen, Jeff Schneider

ICML 2018 Multi-Fidelity Black-Box Optimization with Hierarchical Partitions Rajat Sen, Kirthevasan Kandasamy, Sanjay Shakkottai

NeurIPS 2018 Neural Architecture Search with Bayesian Optimisation and Optimal Transport Kirthevasan Kandasamy, Willie Neiswanger, Jeff Schneider, Barnabas Poczos, Eric P Xing

AISTATS 2018 Parallelised Bayesian Optimisation via Thompson Sampling Kirthevasan Kandasamy, Akshay Krishnamurthy, Jeff Schneider, Barnabás Póczos

ICLR 2017 Batch Policy Gradient Methods for Improving Neural Conversation Models Kirthevasan Kandasamy, Yoram Bachrach, Ryota Tomioka, Daniel Tarlow, David Carter

ICML 2017 Multi-Fidelity Bayesian Optimisation with Continuous Approximations Kirthevasan Kandasamy, Gautam Dasarathy, Jeff Schneider, Barnabás Póczos

ICML 2016 Additive Approximations in High Dimensional Nonparametric Regression via the SALSA Kirthevasan Kandasamy, Yaoliang Yu

NeurIPS 2016 Gaussian Process Bandit Optimisation with Multi-Fidelity Evaluations Kirthevasan Kandasamy, Gautam Dasarathy, Junier B Oliva, Jeff Schneider, Barnabas Poczos

AISTATS 2016 High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models Chun-Liang Li, Kirthevasan Kandasamy, Barnabás Póczos, Jeff G. Schneider

NeurIPS 2016 Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices Kirthevasan Kandasamy, Maruan Al-Shedivat, Eric P Xing

NeurIPS 2016 The Multi-Fidelity Multi-Armed Bandit Kirthevasan Kandasamy, Gautam Dasarathy, Barnabas Poczos, Jeff Schneider

IJCAI 2015 Bayesian Active Learning for Posterior Estimation - IJCAI-15 Distinguished Paper Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos

ICML 2015 High Dimensional Bayesian Optimisation and Bandits via Additive Models Kirthevasan Kandasamy, Jeff Schneider, Barnabas Poczos

NeurIPS 2015 Nonparametric Von Mises Estimators for Entropies, Divergences and Mutual Informations Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabas Poczos, Larry Wasserman, James M Robins

AISTATS 2015 On Estimating L22 Divergence Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabás Póczos, Larry A. Wasserman

ICML 2014 Nonparametric Estimation of Renyi Divergence and Friends Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabas Poczos, Larry Wasserman