Mikhail Khodak

According to our database¹, Mikhail Khodak authored at least 32 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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PhD thesis

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On csauthors.net:

Bibliography

2024

Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Meta-Learning Adversarial Bandit Algorithms.

[BibT_eX]

[DOI]

CoRR, 2023

On Noisy Evaluation in Federated Hyperparameter Tuning.

[BibT_eX]

[DOI]

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

Cross-Modal Fine-Tuning: Align then Refine.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Learning-augmented private algorithms for multiple quantile release.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Meta-Learning in Games.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

AANG : Automating Auxiliary Learning.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Private Algorithms with Private Predictions.

[BibT_eX]

[DOI]

CoRR, 2022

Provably tuning the ElasticNet across instances.

[BibT_eX]

[DOI]

CoRR, 2022

Meta-Learning Adversarial Bandits.

[BibT_eX]

[DOI]

CoRR, 2022

Learning Predictions for Algorithms with Predictions.

[BibT_eX]

[DOI]

CoRR, 2022

NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Tasks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficient Architecture Search for Diverse Tasks.

[BibT_eX]

[DOI]

Junhong Shen

Mikhail Khodak

Ameet Talwalkar

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Advances and Open Problems in Federated Learning.

[BibT_eX]

[DOI]

Rafael G. L. D'Oliveira

Ananda Theertha Suresh

Found. Trends Mach. Learn., 2021

NAS-Bench-360: Benchmarking Diverse Tasks for Neural Architecture Search.

[BibT_eX]

[DOI]

CoRR, 2021

Rethinking Neural Operations for Diverse Tasks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

AutoML Decathlon: Diverse Tasks, Modern Methods, and Efficiency at Scale.

[BibT_eX]

[DOI]

Proceedings of the NeurIPS 2022 Competition Track, 2021

Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning-to-learn non-convex piecewise-Lipschitz functions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Geometry-Aware Gradient Algorithms for Neural Architecture Search.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Initialization and Regularization of Factorized Neural Layers.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

A Sample Complexity Separation between Non-Convex and Convex Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Differentially Private Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Advances and Open Problems in Federated Learning.

[BibT_eX]

[DOI]

Rafael G. L. D'Oliveira

Ananda Theertha Suresh

CoRR, 2019

Adaptive Gradient-Based Meta-Learning Methods.

[BibT_eX]

[DOI]

Mikhail Khodak

Maria-Florina Balcan

Ameet Talwalkar

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Theoretical Analysis of Contrastive Unsupervised Representation Learning.

[BibT_eX]

[DOI]

Hrishikesh Khandeparkar

Proceedings of the 36th International Conference on Machine Learning, 2019

Provable Guarantees for Gradient-Based Meta-Learning.

[BibT_eX]

[DOI]

Maria-Florina Balcan

Mikhail Khodak

Ameet Talwalkar

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

A Large Self-Annotated Corpus for Sarcasm.

[BibT_eX]

[DOI]

Mikhail Khodak

Nikunj Saunshi

Kiran Vodrahalli

Proceedings of the Eleventh International Conference on Language Resources and Evaluation, 2018

Learning Cloud Dynamics to Optimize Spot Instance Bidding Strategies.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Communications, 2018

A Compressed Sensing View of Unsupervised Text Embeddings, Bag-of-n-Grams, and LSTMs.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors.

[BibT_eX]

[DOI]

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017

Extending and Improving Wordnet via Unsupervised Word Embeddings.

[BibT_eX]

[DOI]

CoRR, 2017

Mikhail Khodak

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