Ashwin Pananjady
15 papers · 2018–2026 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (30) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Keyword Champion
(2)
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Keyword Collector
(70)
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Trend Setter
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Century Club Β· Bronze
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Research topics
Machine Learning
(13)
Optimization & Theory
(9)
Mathematics & Optimization
(6)
Learning Types
(5)
Optimization
(4)
Artificial Intelligence
(3)
Core AI
(3)
Reinforcement Learning
(2)
Core Methods
(2)
Mathematics
(2)
Methods Β· Reinforcement Learning
(2)
Data Science & Analytics
(1)
Application Areas
(1)
Methods Β· Data Science & Analytics
(1)
Keywords
derivative-free optimization
(2)
mixing time
(2)
policy optimization
(2)
inverse reinforcement learning
(2)
markov chain
(2)
linear quadratic system
(2)
conformal prediction
(1)
neural network training
(1)
reinforcement learning
(1)
preference learning
(1)
sample complexity
(1)
distributed learning
(1)
game theory
(1)
nash equilibrium
(1)
policy evaluation
(1)
stochastic approximation
(1)
reward function
(1)
statistical model
(1)
mahalanobis distance
(1)
non-convex optimization
(1)
Papers
Predictive inference for time series: why is split conformal effective despite temporal dependence?
ALT 2026
Computationally efficient reductions between some statistical models
ALT 2025
Estimating stationary mass, frequency by frequency
COLT 2025
Alternating minimization for generalized rank one matrix sensing: Sharp predictions from a random initialization
ALT 2024
Just Wing It: Near-Optimal Estimation of Missing Mass in a Markovian Sequence
JMLR 2024
One Shot Inverse Reinforcement Learning for Stochastic Linear Bandits
UAI 2024
Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning
NeurIPS 2023
Sharp analysis of EM for learning mixtures of pairwise differences
COLT 2023
Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits
AISTATS 2022
Optimal and instance-dependent guarantees for Markovian linear stochastic approximation
COLT 2022
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems
JMLR 2020
Preference learning along multiple criteria: A game-theoretic perspective
NeurIPS 2020
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems
AISTATS 2019
Breaking the 1/βn Barrier: Faster Rates for Permutation-based Models in Polynomial Time
COLT 2018
Gradient Diversity: a Key Ingredient for Scalable Distributed Learning
AISTATS 2018