Prashanth L.A.
11 papers · 2013–2024 · 6 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (17) 🌍 Conference Polyglot · Silver 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge · Silver 🏃 Academic Marathon · Half
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Keyword Champion
(4)
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Trend Setter
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Unstoppable · Bronze
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Century Club · Bronze
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Top co-authors
Research topics
Machine Learning
(10)
Optimization & Theory · Machine Learning
(8)
Application Areas
(7)
Mathematics & Optimization
(5)
Reinforcement Learning
(4)
Methods
(4)
Optimization
(3)
Learning Types
(2)
Mathematics
(2)
Data Science & Analytics
(1)
Deep Learning
(1)
Applications
(1)
Optimization & Theory · Deep Learning
(1)
Probability
(1)
Keywords
concentration bound
(4)
conditional value at risk
(3)
multi-armed bandit
(2)
policy optimization
(2)
reinforcement learning
(2)
value function
(2)
risk measure
(2)
wasserstein distance
(2)
stochastic bandit
(2)
best arm identification
(2)
cumulative prospect theory
(2)
exploration-exploitation tradeoff
(1)
convex optimization
(1)
regret minimization
(1)
markov decision process
(1)
markov decision processes
(1)
sample complexity
(1)
sequential decision making
(1)
mean squared error
(1)
likelihood ratio
(1)
Papers
A Cubic-regularized Policy Newton Algorithm for Reinforcement Learning
AISTATS 2024
Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation
AISTATS 2023
A Survey of Risk-Aware Multi-Armed Bandits
IJCAI 2022
A Wasserstein Distance Approach for Concentration of Empirical Risk Estimates
JMLR 2022
Estimation of Spectral Risk Measures
AAAI 2021
Concentration bounds for CVaR estimation: The cases of light-tailed and heavy-tailed distributions
ICML 2020
Concentration of risk measures: A Wasserstein distance approach
NeurIPS 2019
Correlated bandits or: How to minimize mean-squared error online
ICML 2019
(Bandit) Convex Optimization with Biased Noisy Gradient Oracles
AISTATS 2016
Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control
ICML 2016
Actor-Critic Algorithms for Risk-Sensitive MDPs
NeurIPS 2013