Mikhail Khodak
19 papers · 2018–2025 · 4 venues · across top CS/AI venues
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Machine Learning
(19)
Artificial Intelligence
(9)
Learning Paradigms Β· Artificial Intelligence
(9)
Optimization & Theory
(9)
Application Areas
(8)
Learning Types Β· Machine Learning
(8)
Deep Learning
(6)
Learning Paradigms Β· Machine Learning
(5)
Core Methods
(4)
Learning Types Β· Deep Learning
(4)
Techniques
(3)
Mathematics & Optimization
(2)
Core AI
(2)
Natural Language Processing
(1)
Security & Privacy
(1)
Keywords
transfer learning
(6)
neural architecture search
(3)
federated learning
(3)
domain adaptation
(3)
gradient descent
(2)
differential privacy
(2)
regret bound
(2)
online convex optimization
(2)
representation learning
(2)
non-convex optimization
(2)
sample complexity
(2)
weight sharing
(2)
online learning
(2)
hyperparameter optimization
(1)
game theory
(1)
contrastive learning
(1)
compressed sensing
(1)
unsupervised learning
(1)
supervised learning
(1)
multimodal learning
(1)
Papers
Specialized Foundation Models Struggle to Beat Supervised Baselines
ICLR 2025
Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances
ICLR 2024
SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation
NeurIPS 2024
AANG : Automating Auxiliary Learning
ICLR 2023
Cross-Modal Fine-Tuning: Align then Refine
ICML 2023
Learning-augmented private algorithms for multiple quantile release
ICML 2023
Meta-Learning in Games
ICLR 2023
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing
NeurIPS 2021
Geometry-Aware Gradient Algorithms for Neural Architecture Search
ICLR 2021
Initialization and Regularization of Factorized Neural Layers
ICLR 2021
Learning-to-learn non-convex piecewise-Lipschitz functions
NeurIPS 2021
Rethinking Neural Operations for Diverse Tasks
NeurIPS 2021
A Sample Complexity Separation between Non-Convex and Convex Meta-Learning
ICML 2020
Differentially Private Meta-Learning
ICLR 2020
Adaptive Gradient-Based Meta-Learning Methods
NeurIPS 2019
A Theoretical Analysis of Contrastive Unsupervised Representation Learning
ICML 2019
Provable Guarantees for Gradient-Based Meta-Learning
ICML 2019
A Compressed Sensing View of Unsupervised Text Embeddings, Bag-of-n-Grams, and LSTMs
ICLR 2018
A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors
ACL 2018