Cyril Zhang

According to our database, Cyril Zhang authored at least 33 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Can large language models explore in-context?

Akshay Krishnamurthy, Keegan Harris, Dylan J. Foster, Cyril Zhang, Aleksandrs Slivkins

CoRR, 2024

2023

Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression.

Adam Block, Dylan J. Foster, Akshay Krishnamurthy, Max Simchowitz, Cyril Zhang

CoRR, 2023

Pareto Frontiers in Neural Feature Learning: Data, Compute, Width, and Luck.

Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang

CoRR, 2023

Autocalibrating Gaze Tracking: A Demonstration through Gaze Typing.

Akanksha Saran, Jacob Alber, Danielle Bragg, Cyril Zhang, John Langford

CoRR, 2023

Exposing Attention Glitches with Flip-Flop Language Modeling.

Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck.

Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Transformers Learn Shortcuts to Automata.

Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Understanding and Improving Neural Active Learning on Heteroskedastic Distributions.

Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Learning Hidden Markov Models Using Conditional Samples.

Gaurav Mahajan, Sham M. Kakade, Akshay Krishnamurthy, Cyril Zhang

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Neural Active Learning on Heteroskedastic Distributions.

Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb

CoRR, 2022

Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms.

Surbhi Goel, Sham M. Kakade, Adam Kalai, Cyril Zhang

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

Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit.

Boaz Barak, Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang

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

Understanding Contrastive Learning Requires Incorporating Inductive Biases.

Nikunj Saunshi, Jordan T. Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham M. Kakade, Akshay Krishnamurthy

Proceedings of the International Conference on Machine Learning, 2022

Sparsity in Partially Controllable Linear Systems.

Yonathan Efroni, Sham M. Kakade, Akshay Krishnamurthy, Cyril Zhang

Proceedings of the International Conference on Machine Learning, 2022

Inductive Biases and Variable Creation in Self-Attention Mechanisms.

Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Cyril Zhang

Proceedings of the International Conference on Machine Learning, 2022

Anti-Concentrated Confidence Bonuses For Scalable Exploration.

Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Machine Learning for Mechanical Ventilation Control (Extended Abstract).

Daniel Suo, Cyril Zhang, Paula Gradu, Udaya Ghai, Xinyi Chen, Edgar Minasyan, Naman Agarwal, Karan Singh, Julienne LaChance, Tom Zajdel, Manuel Schottdorf, Daniel J. Cohen, Elad Hazan

CoRR, 2021

Deluca - A Differentiable Control Library: Environments, Methods, and Benchmarking.

Paula Gradu, John Hallman, Daniel Suo, Alex Yu, Naman Agarwal, Udaya Ghai, Karan Singh, Cyril Zhang, Anirudha Majumdar, Elad Hazan

CoRR, 2021

Machine Learning for Mechanical Ventilation Control.

Daniel Suo, Cyril Zhang, Paula Gradu, Udaya Ghai, Xinyi Chen, Edgar Minasyan, Naman Agarwal, Karan Singh, Julienne LaChance, Tom Zajdel, Manuel Schottdorf, Daniel J. Cohen, Elad Hazan

CoRR, 2021

Acceleration via Fractal Learning Rate Schedules.

Naman Agarwal, Surbhi Goel, Cyril Zhang

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Disentangling Adaptive Gradient Methods from Learning Rates.

Naman Agarwal, Rohan Anil, Elad Hazan, Tomer Koren, Cyril Zhang

CoRR, 2020

Stochastic Optimization with Laggard Data Pipelines.

Naman Agarwal, Rohan Anil, Tomer Koren, Kunal Talwar, Cyril Zhang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Calibration, Entropy Rates, and Memory in Language Models.

Mark Braverman, Xinyi Chen, Sham M. Kakade, Karthik Narasimhan, Cyril Zhang, Yi Zhang

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

Extreme Tensoring for Low-Memory Preconditioning.

Xinyi Chen, Naman Agarwal, Elad Hazan, Cyril Zhang, Yi Zhang

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

No-Regret Prediction in Marginally Stable Systems.

Udaya Ghai, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang

Proceedings of the Conference on Learning Theory, 2020

Robust guarantees for learning an autoregressive filter.

Holden Lee, Cyril Zhang

Proceedings of the Algorithmic Learning Theory, 2020

2019

Efficient Full-Matrix Adaptive Regularization.

Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang, Yi Zhang

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

2018

The Case for Full-Matrix Adaptive Regularization.

Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang, Yi Zhang

CoRR, 2018

Spectral Filtering for General Linear Dynamical Systems.

Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Not-So-Random Features.

Brian Bullins, Cyril Zhang, Yi Zhang

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

Towards Provable Control for Unknown Linear Dynamical Systems.

Sanjeev Arora, Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang

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

2017

Learning Linear Dynamical Systems via Spectral Filtering.

Elad Hazan, Karan Singh, Cyril Zhang

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Efficient Regret Minimization in Non-Convex Games.

Elad Hazan, Karan Singh, Cyril Zhang

Proceedings of the 34th International Conference on Machine Learning, 2017