← Authors

Kirthevasan Kandasamy

29 papers · 2014–2026 · 7 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (11) πŸ—ΊοΈ Taxonomy Completionist (13) 🐝 Cross-Pollinator (14) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (6) 🧭 Keyword Pioneer πŸ”¬ Deep Specialist (10) πŸ† Keyword Champion (3) 🀝 Dynamic Duo (14) πŸ—ƒοΈ Keyword Collector (102) ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ’Ž Century Club (28) πŸ”₯ Unstoppable (12) πŸ“ˆ Trend Setter

Conferences

ICML (9) NIPS (8) AISTATS (7) JMLR (2) AAAI (1) OSDI (1) UAI (1)

Top co-authors

BarnabΓ‘s PΓ³czos (14) Jeff Schneider (11) Willie Neiswanger (5) Akshay Krishnamurthy (5) Ion Stoica (4) Larry Wasserman (3) Joseph Gonzalez (3) Gautam Dasarathy (3) Michael Jordan (3) Eric P. Xing (3)

Research topics

Statistics (1)

Keywords

regret bound (9) multi-armed bandit (8) bayesian optimization (8) multi-fidelity optimization (5) hyperparameter tuning (5) gaussian process (5) black-box optimization (4) online learning (4) sublinear regret (3) nonparametric estimation (3) resource allocation (3) mechanism design (2) additive model (2) stochastic optimization (2) upper confidence bound (2) neural architecture search (2) hierarchical partitioning (2) optimal transport (2) density estimation (2) active learning (2)

Papers

Constrained Best Arm Identification with Tests for Feasibility AAAI 2026
Collaborative Mean Estimation Among Heterogeneous Strategic Agents: Individual Rationality, Fairness, and Truthful Contribution ICML 2025
Learning to Price Homogeneous Data NIPS 2024
Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning ICML 2024
Active Cost-aware Labeling of Streaming Data AISTATS 2023
Mechanism Design for Collaborative Normal Mean Estimation NIPS 2023
VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit Feedback JMLR 2023
Cilantro: Performance-Aware Resource Allocation for General Objectives via Online Feedback OSDI 2023
Learning Competitive Equilibria in Exchange Economies with Bandit Feedback AISTATS 2022
Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism ICML 2021
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations AISTATS 2020
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly JMLR 2020
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments ICML 2019
Noisy Blackbox Optimization using Multi-fidelity Queries: A Tree Search Approach AISTATS 2019
Offline Contextual Bayesian Optimization NIPS 2019
A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations UAI 2019
Parallelised Bayesian Optimisation via Thompson Sampling AISTATS 2018
Neural Architecture Search with Bayesian Optimisation and Optimal Transport NIPS 2018
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions ICML 2018
Multi-fidelity Bayesian Optimisation with Continuous Approximations ICML 2017
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models AISTATS 2016
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices NIPS 2016
The Multi-fidelity Multi-armed Bandit NIPS 2016
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations NIPS 2016
Additive Approximations in High Dimensional Nonparametric Regression via the SALSA ICML 2016
High Dimensional Bayesian Optimisation and Bandits via Additive Models ICML 2015
On Estimating L_2^2 Divergence AISTATS 2015
Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations NIPS 2015
Nonparametric Estimation of Renyi Divergence and Friends ICML 2014