Ashwin Pananjady
15 papers · 2018–2026 · 6 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (22) π Interdisciplinary Bridge π Conference Polyglot (6)
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Academic Marathon
(7)
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Cross-Pollinator
(8)
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Century Club
(14)
ποΈ
Keyword Collector
(54)
Conferences
COLT (4)
AISTATS (3)
ALT (3)
JMLR (2)
NIPS (2)
UAI (1)
Top co-authors
Keywords
derivative-free optimization
(2)
mixing time
(2)
policy optimization
(2)
markov chain
(2)
conformal prediction
(1)
non-convex optimization
(1)
metric learning
(1)
preference learning
(1)
neural network training
(1)
sample complexity
(1)
distributed learning
(1)
inverse reinforcement learning
(1)
nash equilibrium
(1)
game theory
(1)
mahalanobis distance
(1)
stochastic approximation
(1)
alternating minimization
(1)
low-rank matrix
(1)
rank aggregation
(1)
policy evaluation
(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
One Shot Inverse Reinforcement Learning for Stochastic Linear Bandits
UAI 2024
Just Wing It: Near-Optimal Estimation of Missing Mass in a Markovian Sequence
JMLR 2024
Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning
NIPS 2023
Sharp analysis of EM for learning mixtures of pairwise differences
COLT 2023
Optimal and instance-dependent guarantees for Markovian linear stochastic approximation
COLT 2022
Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits
AISTATS 2022
Preference learning along multiple criteria: A game-theoretic perspective
NIPS 2020
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems
JMLR 2020
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems
AISTATS 2019
Breaking the $1/\sqrt{n}$ Barrier: Faster Rates for Permutation-based Models in Polynomial Time
COLT 2018
Gradient Diversity: a Key Ingredient for Scalable Distributed Learning
AISTATS 2018