Kirthevasan Kandasamy

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 59

Top Topics

Additive Models

Top Venues

Publications

Keran Chen, Joon Suk Huh, Kirthevasan Kandasamy
Learning to Price Homogeneous Data. CoRR (2024)
Joon Suk Huh, Kirthevasan Kandasamy
Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning. CoRR (2024)
Alex Clinton, Yiding Chen, Xiaojin Zhu, Kirthevasan Kandasamy
Data Sharing for Mean Estimation Among Heterogeneous Strategic Agents. CoRR (2024)
Joon Suk Huh, Ellen Vitercik, Kirthevasan Kandasamy
Bandit Profit-maximization for Targeted Marketing. CoRR (2024)
Kirthevasan Kandasamy, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica
VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit Feedback. J. Mach. Learn. Res. 24 (2023)
Ting Cai, Kirthevasan Kandasamy
Active Cost-aware Labeling of Streaming Data. AISTATS (2023)
Romil Bhardwaj, Kirthevasan Kandasamy, Asim Biswal, Wenshuo Guo, Benjamin Hindman, Joseph Gonzalez, Michael I. Jordan, Ion Stoica
Cilantro: Performance-Aware Resource Allocation for General Objectives via Online Feedback. OSDI (2023)
Ting Cai, Kirthevasan Kandasamy
Active Cost-aware Labeling of Streaming Data. CoRR (2023)
Wenshuo Guo, Nika Haghtalab, Kirthevasan Kandasamy, Ellen Vitercik
Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty. EC (2023)
Yiding Chen, Xiaojin Zhu, Kirthevasan Kandasamy
Mechanism Design for Collaborative Normal Mean Estimation. CoRR (2023)
Wenshuo Guo, Nika Haghtalab, Kirthevasan Kandasamy, Ellen Vitercik
Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty. CoRR (2023)
Yiding Chen, Jerry Zhu, Kirthevasan Kandasamy
Mechanism Design for Collaborative Normal Mean Estimation. NeurIPS (2023)
Wenshuo Guo, Kirthevasan Kandasamy, Joseph Gonzalez, Michael I. Jordan, Ion Stoica
Learning Competitive Equilibria in Exchange Economies with Bandit Feedback. AISTATS (2022)
Ujval Misra, Richard Liaw, Lisa Dunlap, Romil Bhardwaj, Kirthevasan Kandasamy, Joseph E. Gonzalez, Ion Stoica, Alexey Tumanov
RubberBand: cloud-based hyperparameter tuning. EuroSys (2021)
Wenshuo Guo, Kirthevasan Kandasamy, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica
Online Learning of Competitive Equilibria in Exchange Economies. CoRR (2021)
Lisa Dunlap, Kirthevasan Kandasamy, Ujval Misra, Richard Liaw, Michael I. Jordan, Ion Stoica, Joseph E. Gonzalez
Elastic Hyperparameter Tuning on the Cloud. SoCC (2021)
Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael I. Jordan, Ken Goldberg, Joseph E. Gonzalez
PAC Best Arm Identification Under a Deadline. CoRR (2021)
Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael I. Jordan, Ken Goldberg, Joseph Gonzalez
Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism. ICML (2021)
Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael I. Jordan, Ken Goldberg, Joseph E. Gonzalez
Resource Allocation in Multi-armed Bandit Exploration: Overcoming Nonlinear Scaling with Adaptive Parallelism. CoRR (2020)
Adarsh Dave, Jared Mitchell, Kirthevasan Kandasamy, Sven Burke, Biswajit Paria, Barnabás Póczos, Jay Whitacre, Venkatasubramanian Viswanathan
Autonomous discovery of battery electrolytes with robotic experimentation and machine-learning. CoRR (2020)
Kirthevasan Kandasamy, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica
Mechanism Design with Bandit Feedback. CoRR (2020)
Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy, Willie Neiswanger, Barnabás Póczos, Jeff Schneider, Eric P. Xing
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations. AISTATS (2020)
Youngseog Chung, Ian Char, Willie Neiswanger, Kirthevasan Kandasamy, Andrew Oakleigh Nelson, Mark D. Boyer, Egemen Kolemen, Jeff Schneider
Offline Contextual Bayesian Optimization for Nuclear Fusion. CoRR (2020)
Kirthevasan Kandasamy, Gur-Eyal Sela, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica
Online Learning Demands in Max-min Fairness. CoRR (2020)
Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria, Christopher R. Collins, Jeff Schneider, Barnabás Póczos, Eric P. Xing
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly. J. Mach. Learn. Res. 21 (2020)
Ian Char, Youngseog Chung, Willie Neiswanger, Kirthevasan Kandasamy, Oak Nelson, Mark D. Boyer, Egemen Kolemen
Offline Contextual Bayesian Optimization. NeurIPS (2019)
Rajat Sen, Kirthevasan Kandasamy, Sanjay Shakkottai
Noisy Blackbox Optimization using Multi-fidelity Queries: A Tree Search Approach. AISTATS (2019)
Willie Neiswanger, Kirthevasan Kandasamy, Barnabás Póczos, Jeff Schneider, Eric P. Xing
ProBO: a Framework for Using Probabilistic Programming in Bayesian Optimization. CoRR (2019)
Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria, Christopher R. Collins, Jeff Schneider, Barnabás Póczos, Eric P. Xing
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly. CoRR (2019)
Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy, Willie Neiswanger, Barnabás Póczos, Jeff Schneider, Eric P. Xing
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations. CoRR (2019)
Kirthevasan Kandasamy, Willie Neiswanger, Reed Zhang, Akshay Krishnamurthy, Jeff Schneider, Barnabás Póczos
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments. ICML (2019)
Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
Multi-fidelity Gaussian Process Bandit Optimisation. J. Artif. Intell. Res. 66 (2019)
Biswajit Paria, Kirthevasan Kandasamy, Barnabás Póczos
A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations. UAI (2019)
Kirthevasan Kandasamy, Willie Neiswanger, Jeff Schneider, Barnabás Póczos, Eric P. Xing
Neural Architecture Search with Bayesian Optimisation and Optimal Transport. NeurIPS (2018)
Biswajit Paria, Kirthevasan Kandasamy, Barnabás Póczos
A Flexible Multi-Objective Bayesian Optimization Approach using Random Scalarizations. CoRR (2018)
Kirthevasan Kandasamy, Willie Neiswanger, Reed Zhang, Akshay Krishnamurthy, Jeff Schneider, Barnabás Póczos
Myopic Bayesian Design of Experiments via Posterior Sampling and Probabilistic Programming. CoRR (2018)
Kirthevasan Kandasamy, Willie Neiswanger, Jeff Schneider, Barnabás Póczos, Eric P. Xing
Neural Architecture Search with Bayesian Optimisation and Optimal Transport. CoRR (2018)
Rajat Sen, Kirthevasan Kandasamy, Sanjay Shakkottai
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions. ICML (2018)
Rajat Sen, Kirthevasan Kandasamy, Sanjay Shakkottai
Noisy Blackbox Optimization with Multi-Fidelity Queries: A Tree Search Approach. CoRR (2018)
Kirthevasan Kandasamy, Akshay Krishnamurthy, Jeff Schneider, Barnabás Póczos
Parallelised Bayesian Optimisation via Thompson Sampling. AISTATS (2018)
Kirthevasan Kandasamy, Yoram Bachrach, Ryota Tomioka, Daniel Tarlow, David Carter
Batch Policy Gradient Methods for Improving Neural Conversation Models. CoRR (2017)
Kirthevasan Kandasamy, Gautam Dasarathy, Jeff G. Schneider, Barnabás Póczos
Multi-fidelity Bayesian Optimisation with Continuous Approximations. ICML (2017)
Kirthevasan Kandasamy, Akshay Krishnamurthy, Jeff G. Schneider, Barnabás Póczos
Asynchronous Parallel Bayesian Optimisation via Thompson Sampling. CoRR (2017)
Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos
Query efficient posterior estimation in scientific experiments via Bayesian active learning. Artif. Intell. 243 (2017)
Kirthevasan Kandasamy, Yoram Bachrach, Ryota Tomioka, Daniel Tarlow, David Carter
Batch Policy Gradient Methods for Improving Neural Conversation Models. ICLR (Poster) (2017)
Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations. NIPS (2016)
Kirthevasan Kandasamy, Gautam Dasarathy, Jeff G. Schneider, Barnabás Póczos
The Multi-fidelity Multi-armed Bandit. CoRR (2016)
Kirthevasan Kandasamy, Maruan Al-Shedivat, Eric P. Xing
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices. NIPS (2016)
Chun-Liang Li, Kirthevasan Kandasamy, Barnabás Póczos, Jeff G. Schneider
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models. AISTATS (2016)
Kirthevasan Kandasamy, Maruan Al-Shedivat, Eric P. Xing
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices. CoRR (2016)
Kirthevasan Kandasamy, Yaoliang Yu
Additive Approximations in High Dimensional Nonparametric Regression via the SALSA. ICML (2016)
Kirthevasan Kandasamy, Gautam Dasarathy, Barnabás Póczos, Jeff G. Schneider
The Multi-fidelity Multi-armed Bandit. NIPS (2016)
Kirthevasan Kandasamy, Yaoliang Yu
Additive Approximations in High Dimensional Nonparametric Regression via the SALSA. CoRR (2016)
Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
Multi-fidelity Gaussian Process Bandit Optimisation. CoRR (2016)
Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabás Póczos, Larry A. Wasserman
On Estimating L22 Divergence. AISTATS (2015)
Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, Larry A. Wasserman, James M. Robins
Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations. NIPS (2015)
Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos
High Dimensional Bayesian Optimisation and Bandits via Additive Models. ICML (2015)
Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos
Bayesian Active Learning for Posterior Estimation - IJCAI-15 Distinguished Paper. IJCAI (2015)
Kirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos
High Dimensional Bayesian Optimisation and Bandits via Additive Models. CoRR (2015)
Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, Larry A. Wasserman, James M. Robins
Influence Functions for Machine Learning: Nonparametric Estimators for Entropies, Divergences and Mutual Informations. CoRR (2014)
Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabás Póczos, Larry A. Wasserman
Nonparametric Estimation of Renyi Divergence and Friends. ICML (2014)
Kirthevasan Kandasamy
Latent Beta Topographic Mapping. ICTAI (2012)