All alphabetical author orderings were determined alphabetically.
"*" denotes equal contribution.

**A Deeper Look at Zero-Cost Proxies for Lightweight NAS. ICLR 2022 (Blog Track).**

Colin White, Mikhail Khodak, Renbo Tu, Shital Shah, Sébastien Bubeck, Debadeepta Dey.

[post]

**Rethinking Neural Operations for Diverse Tasks. NeurIPS 2021.**

Nicholas Roberts*, Mikhail Khodak*, Tri Dao, Liam Li, Christopher Ré, Ameet Talwalkar.

[paper]
[arXiv]
[code]
[slides]
[talk]
[Python package]

**Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing. NeurIPS 2021.**

Mikhail Khodak, Renbo Tu, Tian Li, Liam Li, Maria-Florina Balcan, Virginia Smith, Ameet Talwalkar.

[paper]
[arXiv]
[code]
[poster]
[slides]
[talk]

**Learning-to-Learn Non-Convex Piecewise-Lipschitz Functions. NeurIPS 2021.**

Maria-Florina Balcan, Mikhail Khodak, Dravyansh Sharma, Ameet Talwalkar.

[paper]
[arXiv]

**Geometry-Aware Gradient Algorithms for Neural Architecture Search. ICLR 2021.**

Liam Li*, Mikhail Khodak*, Maria-Florina Balcan, Ameet Talwalkar.

[paper]
[arXiv]
[slides]
[code]
[blog]
[talk]
[Determined]

**Initialization and Regularization of Factorized Neural Layers. ICLR 2021.**

Mikhail Khodak, Neil Tenenholtz, Lester Mackey, Nicolò Fusi.

[paper]
[code]
[blog]
[talk]

**A Sample Complexity Separation between Non-Convex and Convex Meta-Learning. ICML 2020.**

Nikunj Saunshi, Yi Zhang, Mikhail Khodak, Sanjeev Arora.

[paper]
[arXiv]
[talk]

**Differentially Private Meta-Learning. ICLR 2020.**

Jeffrey Li, Mikhail Khodak, Sebastian Caldas, Ameet Talwalkar.

[paper]
[arXiv]
[slides]

**Adaptive Gradient-Based Meta-Learning Methods. NeurIPS 2019.**

Mikhail Khodak, Maria-Florina Balcan, Ameet Talwalkar.

[paper]
[arXiv]
[poster]
[slides]
[code]
[blog]
[talk]

**A Theoretical Analysis of Contrastive Unsupervised Representation Learning. ICML 2019.**

Sanjeev Arora, Hrishikesh Khandeparkar, Mikhail Khodak, Orestis Plevrakis, Nikunj Saunshi.

[paper]
[arXiv]
[poster]
[slides]
[data]
[blog]
[talk]

**Provable Guarantees for Gradient-Based Meta-Learning. ICML 2019.**

Mikhail Khodak, Maria-Florina Balcan, Ameet Talwalkar.

[paper]
[arXiv]
[poster]
[code]
[data]

**A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors. ACL 2018.**

Mikhail Khodak*, Nikunj Saunshi*, Yingyu Liang, Tengyu Ma, Brandon Stewart, Sanjeev Arora.

[paper]
[arXiv]
[slides]
[code]
[data]
[blog]
[talk]
[R package]

**A Compressed Sensing View of Unsupervised Text Embeddings, Bag-of-n-Grams, and LSTMs. ICLR 2018.**

Sanjeev Arora, Mikhail Khodak, Nikunj Saunshi, Kiran Vodrahalli.

[paper]
[poster]
[slides]
[code]
[data]
[blog]

**A Large Self-Annotated Corpus for Sarcasm. LREC 2018.**

Mikhail Khodak, Nikunj Saunshi, Kiran Vodrahalli.

[paper]
[arXiv]
[code]
[data]
[CBC]
[Quartz]
[The Register]

**Learning Cloud Dynamics to Optimize Spot Instance Bidding Strategies. INFOCOM 2018.**

Mikhail Khodak, Liang Zheng, Andrew S. Lan, Carlee Joe-Wong, Mung Chiang.

[paper]
[supplement]
[slides]