Kirthevasan Kandasamy
30 papers · 2014–2026 · 8 conferences · across top CS/AI conferences
Achievements
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🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (13) 🌍 Conference Polyglot (6)
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Conference Polyglot
(6)
🧭
Keyword Pioneer
🔬
Deep Specialist
(10)
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(3)
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Dynamic Duo
(14)
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Keyword Collector
(102)
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Prolific Year
(5)
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Conference Pioneer
💎
Century Club
(28)
🔥
Unstoppable
(12)
📈
Trend Setter
Conferences
ICML (9)
NIPS (8)
AISTATS (7)
JMLR (2)
AAAI (1)
ALT (1)
OSDI (1)
UAI (1)
Top co-authors
Research topics
Keywords
regret bound
(9)
multi-armed bandit
(8)
bayesian optimization
(8)
hyperparameter tuning
(5)
multi-fidelity optimization
(5)
gaussian process
(5)
online learning
(5)
black-box optimization
(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
Strategy-robust Online Learning in Contextual Pricing
ALT 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
Cilantro: Performance-Aware Resource Allocation for General Objectives via Online Feedback
OSDI 2023
Mechanism Design for Collaborative Normal Mean Estimation
NIPS 2023
Active Cost-aware Labeling of Streaming Data
AISTATS 2023
VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit Feedback
JMLR 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
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly
JMLR 2020
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations
AISTATS 2020
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments
ICML 2019
A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations
UAI 2019
Offline Contextual Bayesian Optimization
NIPS 2019
Noisy Blackbox Optimization using Multi-fidelity Queries: A Tree Search Approach
AISTATS 2019
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
NIPS 2018
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions
ICML 2018
Parallelised Bayesian Optimisation via Thompson Sampling
AISTATS 2018
Multi-fidelity Bayesian Optimisation with Continuous Approximations
ICML 2017
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
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices
NIPS 2016
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models
AISTATS 2016
Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations
NIPS 2015
On Estimating L_2^2 Divergence
AISTATS 2015
High Dimensional Bayesian Optimisation and Bandits via Additive Models
ICML 2015
Nonparametric Estimation of Renyi Divergence and Friends
ICML 2014