Kannan Ramchandran
29 papers · 2015–2025 · 7 conferences · across top CS/AI conferences
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Conferences
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AISTATS (5)
ICML (4)
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JMLR (1)
OSDI (1)
UAI (1)
Top co-authors
Keywords
imitation learning
(3)
pairwise comparison
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sample complexity
(2)
markov process
(2)
quality estimation
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collaborative filtering
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behavior cloning
(2)
distributed learning
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minimax bounds
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generalization performance
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active learning
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thurstone model
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online learning
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function approximation
(1)
policy gradient
(1)
multi-task learning
(1)
graph clustering
(1)
statistical learning theory
(1)
double descent
(1)
game theory
(1)
Papers
Online Assortment and Price Optimization Under Contextual Choice Models
AISTATS 2025
VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data
ICML 2025
SPEX: Scaling Feature Interaction Explanations for LLMs
ICML 2025
Looped Transformers for Length Generalization
ICLR 2025
EmbedLLM: Learning Compact Representations of Large Language Models
ICLR 2025
Learning to Understand: Identifying Interactions via the MΓΆbius Transform
NIPS 2024
Transformers on Markov data: Constant depth suffices
NIPS 2024
An Analysis of Tokenization: Transformers under Markov Data
NIPS 2024
Online Pricing for Multi-User Multi-Item Markets
NIPS 2023
Learning a 1-layer conditional generative model in total variation
NIPS 2023
Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing
NIPS 2023
Interactive Learning with Pricing for Optimal and Stable Allocations in Markets
AISTATS 2023
Minimax Optimal Online Imitation Learning via Replay Estimation
NIPS 2022
LocalNewton: Reducing communication rounds for distributed learning
UAI 2021
On the Value of Interaction and Function Approximation in Imitation Learning
NIPS 2021
Taxonomizing local versus global structure in neural network loss landscapes
NIPS 2021
An Efficient Framework for Clustered Federated Learning
NIPS 2020
Boundary thickness and robustness in learning models
NIPS 2020
Toward the Fundamental Limits of Imitation Learning
NIPS 2020
Approximate Ranking from Pairwise Comparisons
AISTATS 2018
Gradient Diversity: a Key Ingredient for Scalable Distributed Learning
AISTATS 2018
The Sample Complexity of Online One-Class Collaborative Filtering
ICML 2017
Metadata-conscious anonymous messaging
ICML 2016
Cyclades: Conflict-free Asynchronous Machine Learning
NIPS 2016
Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence
JMLR 2016
EC-Cache: Load-Balanced, Low-Latency Cluster Caching with Online Erasure Coding
OSDI 2016
Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence
AISTATS 2015
An Active Learning Framework using Sparse-Graph Codes for Sparse Polynomials and Graph Sketching
NIPS 2015
Parallel Correlation Clustering on Big Graphs
NIPS 2015