Mikhail Khodak | DeepAI

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∙ 07/05/2023

Meta-Learning Adversarial Bandit Algorithms

We study online meta-learning with bandit feedback, with the goal of imp...

0 Mikhail Khodak, et al. ∙

∙ 02/11/2023

Cross-Modal Fine-Tuning: Align then Refine

Fine-tuning large-scale pretrained models has led to tremendous progress...

0 Junhong Shen, et al. ∙

∙ 12/17/2022

On Noisy Evaluation in Federated Hyperparameter Tuning

Hyperparameter tuning is critical to the success of federated learning a...

0 Kevin Kuo, et al. ∙

∙ 10/20/2022

Private Algorithms with Private Predictions

When applying differential privacy to sensitive data, a common way of ge...

0 Kareem Amin, et al. ∙

∙ 09/28/2022

Meta-Learning in Games

In the literature on game-theoretic equilibrium finding, focus has mainl...

0 Keegan Harris, et al. ∙

∙ 07/20/2022

Provably tuning the ElasticNet across instances

An important unresolved challenge in the theory of regularization is to ...

0 Maria-Florina Balcan, et al. ∙

∙ 05/27/2022

Meta-Learning Adversarial Bandits

We study online learning with bandit feedback across multiple tasks, wit...

0 Maria-Florina Balcan, et al. ∙

∙ 05/27/2022

AANG: Automating Auxiliary Learning

When faced with data-starved or highly complex end-tasks, it is commonpl...

0 Lucio M. Dery, et al. ∙

∙ 04/15/2022

Efficient Architecture Search for Diverse Tasks

While neural architecture search (NAS) has enabled automated machine lea...

0 Junhong Shen, et al. ∙

∙ 02/18/2022

Learning Predictions for Algorithms with Predictions

A burgeoning paradigm in algorithm design is the field of algorithms wit...

0 Mikhail Khodak, et al. ∙

∙ 10/12/2021

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

Most existing neural architecture search (NAS) benchmarks and algorithms...

0 Renbo Tu, et al. ∙

∙ 08/19/2021

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

We analyze the meta-learning of the initialization and step-size of lear...

0 Maria-Florina Balcan, et al. ∙

∙ 06/08/2021

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

Tuning hyperparameters is a crucial but arduous part of the machine lear...

0 Mikhail Khodak, et al. ∙

∙ 05/03/2021

Initialization and Regularization of Factorized Neural Layers

Factorized layers–operations parameterized by products of two or more ma...

0 Mikhail Khodak, et al. ∙

∙ 03/29/2021

Rethinking Neural Operations for Diverse Tasks

An important goal of neural architecture search (NAS) is to automate-awa...

7 Nicholas Roberts, et al. ∙

∙ 04/16/2020

Geometry-Aware Gradient Algorithms for Neural Architecture Search

Many recent state-of-the-art methods for neural architecture search (NAS...

23 Liam Li, et al. ∙

∙ 02/25/2020

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

One popular trend in meta-learning is to learn from many training tasks ...

12 Nikunj Saunshi, et al. ∙

∙ 12/10/2019

Advances and Open Problems in Federated Learning

Federated learning (FL) is a machine learning setting where many clients...

33 Peter Kairouz, et al. ∙

∙ 09/12/2019

Differentially Private Meta-Learning

Parameter-transfer is a well-known and versatile approach for meta-learn...

5 Jeffrey Li, et al. ∙

∙ 06/06/2019

Adaptive Gradient-Based Meta-Learning Methods

We build a theoretical framework for understanding practical meta-learni...

0 Mikhail Khodak, et al. ∙

∙ 02/27/2019

Provable Guarantees for Gradient-Based Meta-Learning

We study the problem of meta-learning through the lens of online convex ...

14 Mikhail Khodak, et al. ∙

∙ 02/25/2019

A Theoretical Analysis of Contrastive Unsupervised Representation Learning

Recent empirical works have successfully used unlabeled data to learn fe...

34 Sanjeev Arora, et al. ∙

∙ 05/14/2018

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

Motivations like domain adaptation, transfer learning, and feature learn...

0 Mikhail Khodak, et al. ∙

∙ 04/29/2017

Extending and Improving Wordnet via Unsupervised Word Embeddings

This work presents an unsupervised approach for improving WordNet that b...

0 Mikhail Khodak, et al. ∙

∙ 04/19/2017

A Large Self-Annotated Corpus for Sarcasm

We introduce the Self-Annotated Reddit Corpus (SARC), a large corpus for...

0 Mikhail Khodak, et al. ∙

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