Rahul Singh
15 papers · 2013–2026 · 9 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+7 more ↓ Show less ↑
🐝 Cross-Pollinator (6) 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (12) 🌍 Conference Polyglot (9) 🌈 Renaissance Researcher (7)
🏃
Academic Marathon
(12)
🐝
Cross-Pollinator
(6)
🏆
Keyword Champion
🗃️
Keyword Collector
(62)
🚀
Conference Pioneer
💎
Century Club
(14)
⚡
Prolific Year
(6)
Conferences
EMNLP (3)
L4DC (3)
AAAI (2)
NIPS (2)
COLING (1)
ICML (1)
JMLR (1)
NSDI (1)
UAI (1)
Top co-authors
Keywords
regret bound
(4)
markov decision process
(3)
named entity recognition
(2)
distributional reinforcement learning
(2)
transformer model
(2)
policy gradient
(2)
adaptive control
(2)
data augmentation
(1)
bert model
(1)
reinforcement learning
(1)
text representation
(1)
parallel corpus
(1)
citation analysis
(1)
text classification
(1)
adaptive discretization
(1)
nonparametric regression
(1)
reproducing kernel hilbert space
(1)
maximum likelihood estimation
(1)
thompson sampling
(1)
neural machine translation
(1)
Papers
Policy Zooming: Adaptive Discretization-based Infinite-Horizon Average-Reward Reinforcement Learning
AAAI 2026
On the Utility of Equal Batch Sizes for Inference in Stochastic Gradient Descent
JMLR 2025
Provably Adaptive Average Reward Reinforcement Learning for Metric Spaces
UAI 2025
Finite Time Logarithmic Regret Bounds for Self-Tuning Regulation
ICML 2024
Sample-based Distributional Policy Gradient
L4DC 2022
Reinforcement Learning Augmented Asymptotically Optimal Index Policy for Finite-Horizon Restless Bandits
AAAI 2022
CNLP-NITS-PP at MixMT 2022: Hinglish-English Code-Mixed Machine Translation
EMNLP 2022
Augmented RBMLE-UCB Approach for Adaptive Control of Linear Quadratic Systems
NIPS 2022
Investigation of English to Hindi Multimodal Neural Machine Translation using Transliteration-based Phrase Pairs Augmentation
COLING 2022
CNLP-NITS-PP at WANLP 2022 Shared Task: Propaganda Detection in Arabic using Data Augmentation and AraBERT Pre-trained Model
EMNLP 2022
Reward Biased Maximum Likelihood Estimation for Reinforcement Learning
L4DC 2021
Improving Robustness via Risk Averse Distributional Reinforcement Learning
L4DC 2020
CiteQA@CLSciSumm 2020
EMNLP 2020
Kernel Instrumental Variable Regression
NIPS 2019
Yank: Enabling Green Data Centers to Pull the Plug
NSDI 2013