Kirthevasan Kandasamy (original) (raw)
[preprints] [publications] [theses] [invited talks]
Denotes joint lead authors, Denotes alphabetical order.
Preprints
Data Sharing for Mean Estimation Among Heterogeneous Strategic Agents
, , ,
[arxiv]
Online Learning Demands in Max-min Fairness
, , , ,
[arxiv] [Simons talk: slides]
Publications
Learning to Price Homogeneous Data
, ,
Advances in Neural Information Processing Systems (NeurIPS) 2024 [arxiv]
Bandit Profit Maximization for Targeted Marketing
, ,
ACM Conference on Economics and Computation (EC) 2024 [arxiv]
Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning
,
International Conference on Machine Learning (ICML) 2024 [pdf]
Mechanism Design for Collaborative Normal Mean Estimation
, ,
Advances in Neural Information Processing Systems (NeurIPS) 2023 [arxiv] [Stanford slides]
Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty
, , ,
ACM Conference on Economics and Computation (EC) 2023 [arxiv] [EC talk: slides] [WSB talk: slides]
🏆 Exemplary Artificial Intelligence Track paper (link)
Cilantro: A Framework for Performance-Aware Resource Allocation for General Objectives via Online Feedback
, , , , , ,
Operating Systems Design and Implementation (OSDI) 2023 [pdf]
Active Cost-aware Labeling of Streaming Data
, ,
International Conference on Artificial Intelligence and Statistics (AISTATS) 2023 [pdf]
VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit Feedback
, , ,
Journal of Machine Learning Research (JMLR) 2022, to appear [pdf]
Online Learning of Competitive Equilibria in Exchange Economies
, , , ,
International Conference on Artificial Intelligence and Statistics (AISTATS) 2022 [arxiv]
Elastic Hyperparameter Tuning on the Cloud
, , , , , ,
Symposium on Cloud Computing (SoCC) 2021 [pdf]
Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism
, , , , ,
International Conference on Machine Learning (ICML) 2021 [arxiv] [Google talk: slides,video]
RubberBand: Cloud-based Hyperparameter Tuning
, , , , , , ,
European Conference on Computer Systems (EuroSys) 2021 [pdf]
Autonomous Discovery of Battery Electrolytes with Robotic Experimentation and Machine Learning
, , , Han Wang, Sven Burke, , , ,
Cell Reports - Physical Science 2020 [pdf] [code,data]
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly
, , , , , , ,
Journal of Machine Learning Research (JMLR) 2020 [pdf] [code,data]
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations
, , , , , ,
International Conference on Artificial Intelligence and Statistics (AISTATS) 2020 [arxiv] [code]
Offline Contextual Bayesian Optimization
, , , , , , ,
Advances in Neural Information Processing Systems (NeurIPS) 2019 [pdf - coming soon]
Multi-fidelity Gaussian Process Bandit Optimisation
, , , ,
Journal of Artificial Intelligence Research (JAIR) 2019 [pdf] [code] [École slides]
Abridged version at: Neural Information Processing Systems (NeurIPS) 2016 [pdf]
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments
, , , , ,
International Conference on Machine Learning (ICML) 2019 [pdf] [code]
A Flexible Multi-Objective Bayesian Optimization Approach using Random Scalarizations
, ,
Conference on Uncertainty in Artificial Intelligence (UAI) 2019 [pdf] [code]
Noisy Blackbox Optimization with Multi-Fidelity Queries: A Tree Search Approach
, ,
International Conference on Artificial Intelligence and Statistics (AISTATS) 2019 [pdf]
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
, , , ,
Advances in Neural Information Processing Systems (NeurIPS) 2018 [pdf] [code,data] [spotlight video] [Uber slides]
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions
, ,
International Conference on Machine Learning (ICML) 2018 [pdf]
Parallelised Bayesian Optimisation via Thompson Sampling
, , ,
International Conference on Artificial Intelligence and Statistics (AISTATS) 2018 [pdf] [code] [AISTATS slides]
Multi-fidelity Bayesian Optimisation with Continuous Approximations
, , ,
International Conference on Machine Learning (ICML) 2017 [pdf] [slides] [talk: video]
Batch Policy Gradient Methods for Improving Neural Conversation Models
, , , ,
International Conference on Learning Representations (ICLR) 2017 [pdf]
Query Efficient Posterior Estimation in Scientific Experiments via Bayesian Active Learning
, ,
Artificial Intelligence Journal (AIJ) 2017 [aij] [arxiv] [code (from David Fleming)]
Abridged version at: International Joint Conference on Artificial Intelligence (IJCAI) 2015 [pdf]
🏆 IJCAI 2015 Distinguished Paper Award (Top 2 out of 1996 submissions, link)
The Multi-fidelity Multi-armed Bandit
, , ,
Advances in Neural Information Processing Systems (NeurIPS) 2016 [pdf]
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices
, ,
Advances in Neural Information Processing Systems (NeurIPS) 2016 [pdf] [code]
Additive Approximations in High Dimensional Nonparametric Regression via the SALSA
,
International Conference on Machine Learning (ICML) 2016 [pdf] [code] [talk: video]
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models
, , ,
International Conference on Artificial Intelligence and Statistics (AISTATS) 2016 [pdf]
Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations
, , , ,
Advances in Neural Information Processing Systems (NeurIPS) 2015 [pdf]
High Dimensional Bayesian Optimisation and Bandits via Additive Models
, ,
International Conference on Machine Learning (ICML) 2015 [pdf] [code] [talk: video,slides]
On Estimating L22 Divergence
, , ,
International Conference on Artificial Intelligence and Statistics (AISTATS) 2015 [pdf]
Nonparametric Estimation of Renyi-Divergence and Friends
, , ,
International Conference on Machine Learning (ICML) 2014 [pdf]
Latent Beta Topographic Mapping
International Conference on Tools with Artificial Intelligence 2012 [pdf]
Unpublished
PAC Best Arm Identification Under a Deadline
, , , , ,
[arxiv] [Google talk: slides,video]
ProBO: A Framework for Using Probabilistic Programming in Bayesian Optimization
, , ,
[arxiv]
Theses
Tuning Hyperparameters without Grad Students: Scaling Up Bandit Optimisation
School of Computer Science, Carnegie Mellon University, October 2018 [pdf]
Invited Talks
Data without Borders: Game-theoretic Challenges in Democratizing Data
Midwest Machine Learnining Symposium, Minneapolis, MN May 2024 [slides]
Longer version at Wisconsin Statistics Seminar, April 2024 [slides]
Mechanism Design for Collabrative Normal Mean Estimation
Stanford University, Palo Alto, CA April 2024 [slides]
Frontiers in Machine Learning and Game Theory
University of Moratuwa, Moratuwa, Sri Lanka, January 2024 [slides]
Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty
Wisconsin School of Business Seminar, Madison, WI February 2023 [slides]
Learning with (Bandit) Feedback from Strategic Stakeholders in Fair Division
Simons Institute, Berkeley, CA May 2022 [slides]
Resource Allocation in Multi-armed Bandits
Google Research, June 2021 [slides,video]
Bayesian Methods for Adaptive Experimentation
Symposium on Autonomous Experimentation, University of Maryland, College Park, MD August 2019 [slides]
Scaling up Bandits and Friends
UC Berkeley, Berkeley, CA April 2019 [slides]
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
Uber AI Labs, San Francisco, CA November 2018 [slides]
Design of Experiments via Probabilistic Modeling: Applications in Materials Science, Model Selection, and Astrophysics
Covestro, Pittsburgh, PA, August 2018
Active Bayesian Design of Experiments via Posterior Sampling
Machine Learning in Science & Engineering Conference, Pittsburgh, PA, June 2018 [slides]
Bayesian Design of Experiments via Posterior Sampling
Lawrence Berkeley National Lab, Berkeley, CA, June 2018 [slides]
Scalable Bandit Methods for Hyper-parameter Tuning
Guest Lecture - Machine Learning for Biology, University of Pittsburgh, Pittsburgh, PA, November 2017 [slides]
Bayesian Optimisation for Materials Science
Electrochemical Energy Symposium, Pittsburgh, PA, November 2017 [slides]
Parallelised Bayesian Optimisation via Thompson Sampling
Google Research, Mountain View, CA, September 2017 [slides]
Multi-fidelity Bayesian Optimisation
Facebook Inc., Menlo Park, CA, September 2017 [slides]
Stochastic Bandits
University of Moratuwa, Moratuwa, Sri Lanka, August 2017 [slides]
Bandit Optimisation with Approximations
École Polytechnique, Paris, France, April 2017 [slides]
Multi-fidelity Bandit Optimisation
University College London, London, UK, July 2016 [slides]