Adith Swaminathan
19 papers · 2015–2026 · 7 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Interdisciplinary Bridge π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (14) π Conference Polyglot (7)
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Renaissance Researcher
(9)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π±
Topic Pioneer
π
Grand Slam
π
Keyword Champion
(2)
ποΈ
Keyword Collector
(89)
π
Conference Pioneer
π
Trend Setter
π
Century Club
(18)
π₯
Unstoppable
(7)
β
The Questioner
Conferences
NIPS (6)
ICML (5)
AAAI (3)
UAI (2)
ICLR (1)
IJCAI (1)
JMLR (1)
Top co-authors
Keywords
reinforcement learning
(5)
policy learning
(4)
counterfactual risk minimization
(3)
importance sampling
(3)
policy gradient
(2)
offline reinforcement learning
(2)
bandit feedback
(2)
causal inference
(2)
large language model
(2)
policy optimization
(2)
counterfactual learning
(2)
markov decision process
(2)
propensity scoring
(2)
multi-label classification
(1)
prompt engineering
(1)
matrix factorization
(1)
off-policy evaluation
(1)
transformer architecture
(1)
empirical risk minimization
(1)
sequential decision-making
(1)
Papers
A Course Correction in Steerability Evaluation: Revealing Miscalibration and Side Effects in LLMs
AAAI 2026
Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs
NIPS 2024
On Overcoming Miscalibrated Conversational Priors in LLM-based ChatBots
UAI 2024
How to Solve Contextual Goal-Oriented Problems with Offline Datasets?
NIPS 2024
Hindsight Learning for MDPs with Exogenous Inputs
ICML 2023
Heuristic-Guided Reinforcement Learning
NIPS 2021
Working Memory Graphs
ICML 2020
Metareasoning in Modular Software Systems: On-the-Fly Configuration Using Reinforcement Learning with Rich Contextual Representations
AAAI 2020
Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration
NIPS 2020
Learning Calibratable Policies using Programmatic Style-Consistency
ICML 2020
Off-Policy Policy Gradient with Stationary Distribution Correction
UAI 2019
A Distillation Approach to Data Efficient Individual Treatment Effect Estimation
AAAI 2019
Unbiased Learning-to-Rank with Biased Feedback
IJCAI 2018
Deep Learning with Logged Bandit Feedback
ICLR 2018
Off-policy evaluation for slate recommendation
NIPS 2017
Recommendations as Treatments: Debiasing Learning and Evaluation
ICML 2016
Counterfactual Risk Minimization: Learning from Logged Bandit Feedback
ICML 2015
The Self-Normalized Estimator for Counterfactual Learning
NIPS 2015
Batch Learning from Logged Bandit Feedback through Counterfactual Risk Minimization
JMLR 2015