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ORCIDCyril Zhang
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2020 – today
- 2024
[c24]Adam Block, Dylan J. Foster, Akshay Krishnamurthy, Max Simchowitz, Cyril Zhang:
Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression. ICLR 2024- [i30]Akshay Krishnamurthy, Keegan Harris, Dylan J. Foster, Cyril Zhang, Aleksandrs Slivkins:
Can large language models explore in-context? CoRR abs/2403.15371 (2024) - [i29]Marah I Abdin, Sam Ade Jacobs, Ammar Ahmad Awan, Jyoti Aneja, Ahmed Awadallah, Hany Awadalla, Nguyen Bach, Amit Bahree, Arash Bakhtiari, Harkirat S. Behl, Alon Benhaim, Misha Bilenko, Johan Bjorck, Sébastien Bubeck, Martin Cai, Caio César Teodoro Mendes, Weizhu Chen, Vishrav Chaudhary, Parul Chopra, Allie Del Giorno, Gustavo de Rosa, Matthew Dixon, Ronen Eldan, Dan Iter, Amit Garg, Abhishek Goswami, Suriya Gunasekar, Emman Haider, Junheng Hao, Russell J. Hewett, Jamie Huynh, Mojan Javaheripi, Xin Jin, Piero Kauffmann, Nikos Karampatziakis, Dongwoo Kim, Mahoud Khademi, Lev Kurilenko, James R. Lee, Yin Tat Lee, Yuanzhi Li, Chen Liang, Weishung Liu, Eric Lin, Zeqi Lin, Piyush Madan, Arindam Mitra, Hardik Modi, Anh Nguyen, Brandon Norick, Barun Patra, Daniel Perez-Becker, Thomas Portet, Reid Pryzant, Heyang Qin, Marko Radmilac, Corby Rosset, Sambudha Roy, Olatunji Ruwase, Olli Saarikivi, Amin Saied, Adil Salim, Michael Santacroce, Shital Shah, Ning Shang, Hiteshi Sharma, Xia Song, Masahiro Tanaka, Xin Wang, Rachel Ward, Guanhua Wang, Philipp Witte, Michael Wyatt, Can Xu, Jiahang Xu, Sonali Yadav, Fan Yang, Ziyi Yang, Donghan Yu, Chengruidong Zhang, Cyril Zhang, Jianwen Zhang, Li Lyna Zhang, Yi Zhang, Yue Zhang, Yunan Zhang, Xiren Zhou:
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone. CoRR abs/2404.14219 (2024) - 2023
- [c23]Gaurav Mahajan, Sham M. Kakade, Akshay Krishnamurthy, Cyril Zhang:
Learning Hidden Markov Models Using Conditional Samples. COLT 2023: 2014-2066 - [c22]Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb:
Understanding and Improving Neural Active Learning on Heteroskedastic Distributions. ECAI 2023: 1248-1255 - [c21]Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang:
Transformers Learn Shortcuts to Automata. ICLR 2023 - [c20]Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang:
Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck. NeurIPS 2023 - [c19]Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang:
Exposing Attention Glitches with Flip-Flop Language Modeling. NeurIPS 2023 - [i28]Sham M. Kakade, Akshay Krishnamurthy, Gaurav Mahajan, Cyril Zhang:
Learning Hidden Markov Models Using Conditional Samples. CoRR abs/2302.14753 (2023) - [i27]Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang:
Exposing Attention Glitches with Flip-Flop Language Modeling. CoRR abs/2306.00946 (2023) - [i26]Akanksha Saran, Jacob Alber, Danielle Bragg, Cyril Zhang, John Langford:
Autocalibrating Gaze Tracking: A Demonstration through Gaze Typing. CoRR abs/2307.15039 (2023) - [i25]Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang:
Pareto Frontiers in Neural Feature Learning: Data, Compute, Width, and Luck. CoRR abs/2309.03800 (2023) - [i24]Adam Block, Dylan J. Foster, Akshay Krishnamurthy, Max Simchowitz, Cyril Zhang:
Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression. CoRR abs/2310.11428 (2023) - 2022
- [c18]Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade:
Anti-Concentrated Confidence Bonuses For Scalable Exploration. ICLR 2022 - [c17]Benjamin L. Edelman
, Surbhi Goel, Sham M. Kakade, Cyril Zhang:
Inductive Biases and Variable Creation in Self-Attention Mechanisms. ICML 2022: 5793-5831 - [c16]Yonathan Efroni, Sham M. Kakade, Akshay Krishnamurthy, Cyril Zhang:
Sparsity in Partially Controllable Linear Systems. ICML 2022: 5851-5860 - [c15]Nikunj Saunshi, Jordan T. Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham M. Kakade, Akshay Krishnamurthy:
Understanding Contrastive Learning Requires Incorporating Inductive Biases. ICML 2022: 19250-19286 - [c14]Boaz Barak, Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang:
Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit. NeurIPS 2022 - [c13]Surbhi Goel, Sham M. Kakade, Adam Kalai, Cyril Zhang:
Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms. NeurIPS 2022 - [i23]Nikunj Saunshi, Jordan T. Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham M. Kakade, Akshay Krishnamurthy:
Understanding Contrastive Learning Requires Incorporating Inductive Biases. CoRR abs/2202.14037 (2022) - [i22]Boaz Barak, Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang:
Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit. CoRR abs/2207.08799 (2022) - [i21]Surbhi Goel, Sham M. Kakade, Adam Tauman Kalai, Cyril Zhang:
Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms. CoRR abs/2209.00735 (2022) - [i20]Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang:
Transformers Learn Shortcuts to Automata. CoRR abs/2210.10749 (2022) - [i19]Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb:
Neural Active Learning on Heteroskedastic Distributions. CoRR abs/2211.00928 (2022) - 2021
- [c12]Naman Agarwal, Surbhi Goel, Cyril Zhang:
Acceleration via Fractal Learning Rate Schedules. ICML 2021: 87-99 - [i18]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:
Machine Learning for Mechanical Ventilation Control. CoRR abs/2102.06779 (2021) - [i17]Paula Gradu, John Hallman, Daniel Suo, Alex Yu, Naman Agarwal, Udaya Ghai, Karan Singh, Cyril Zhang, Anirudha Majumdar, Elad Hazan:
Deluca - A Differentiable Control Library: Environments, Methods, and Benchmarking. CoRR abs/2102.09968 (2021) - [i16]Naman Agarwal, Surbhi Goel, Cyril Zhang:
Acceleration via Fractal Learning Rate Schedules. CoRR abs/2103.01338 (2021) - [i15]Yonathan Efroni, Sham M. Kakade, Akshay Krishnamurthy, Cyril Zhang:
Sparsity in Partially Controllable Linear Systems. CoRR abs/2110.06150 (2021) - [i14]Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Cyril Zhang:
Inductive Biases and Variable Creation in Self-Attention Mechanisms. CoRR abs/2110.10090 (2021) - [i13]Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade:
Anti-Concentrated Confidence Bonuses for Scalable Exploration. CoRR abs/2110.11202 (2021) - [i12]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:
Machine Learning for Mechanical Ventilation Control (Extended Abstract). CoRR abs/2111.10434 (2021) - 2020
- [b1]Cyril Zhang:
Regret-Minimizing Algorithms Beyond Classical Optimization and Control. Princeton University, USA, 2020 - [c11]Holden Lee, Cyril Zhang:
Robust guarantees for learning an autoregressive filter. ALT 2020: 490-517 - [c10]Udaya Ghai, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang:
No-Regret Prediction in Marginally Stable Systems. COLT 2020: 1714-1757 - [c9]Xinyi Chen, Naman Agarwal, Elad Hazan, Cyril Zhang, Yi Zhang:
Extreme Tensoring for Low-Memory Preconditioning. ICLR 2020 - [c8]Mark Braverman, Xinyi Chen, Sham M. Kakade, Karthik Narasimhan, Cyril Zhang, Yi Zhang:
Calibration, Entropy Rates, and Memory in Language Models. ICML 2020: 1089-1099 - [c7]Naman Agarwal, Rohan Anil, Tomer Koren, Kunal Talwar, Cyril Zhang:
Stochastic Optimization with Laggard Data Pipelines. NeurIPS 2020 - [i11]Udaya Ghai, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang:
No-Regret Prediction in Marginally Stable Systems. CoRR abs/2002.02064 (2020) - [i10]Naman Agarwal, Rohan Anil, Elad Hazan, Tomer Koren, Cyril Zhang:
Disentangling Adaptive Gradient Methods from Learning Rates. CoRR abs/2002.11803 (2020) - [i9]Naman Agarwal, Rohan Anil, Tomer Koren, Kunal Talwar, Cyril Zhang:
Stochastic Optimization with Laggard Data Pipelines. CoRR abs/2010.13639 (2020)
2010 – 2019
- 2019
- [c6]Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang, Yi Zhang:
Efficient Full-Matrix Adaptive Regularization. ICML 2019: 102-110 - [i8]Xinyi Chen, Naman Agarwal, Elad Hazan, Cyril Zhang, Yi Zhang:
Extreme Tensoring for Low-Memory Preconditioning. CoRR abs/1902.04620 (2019) - [i7]Holden Lee, Cyril Zhang:
Robust guarantees for learning an autoregressive filter. CoRR abs/1905.09897 (2019) - [i6]Mark Braverman, Xinyi Chen, Sham M. Kakade, Karthik Narasimhan, Cyril Zhang, Yi Zhang:
Calibration, Entropy Rates, and Memory in Language Models. CoRR abs/1906.05664 (2019) - 2018
- [c5]Sanjeev Arora, Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang:
Towards Provable Control for Unknown Linear Dynamical Systems. ICLR (Workshop) 2018 - [c4]Brian Bullins, Cyril Zhang, Yi Zhang:
Not-So-Random Features. ICLR (Poster) 2018 - [c3]Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang:
Spectral Filtering for General Linear Dynamical Systems. NeurIPS 2018: 4639-4648 - [i5]Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang:
Spectral Filtering for General Linear Dynamical Systems. CoRR abs/1802.03981 (2018) - [i4]Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang, Yi Zhang:
The Case for Full-Matrix Adaptive Regularization. CoRR abs/1806.02958 (2018) - 2017
- [c2]Elad Hazan, Karan Singh, Cyril Zhang:
Efficient Regret Minimization in Non-Convex Games. ICML 2017: 1433-1441 - [c1]Elad Hazan, Karan Singh, Cyril Zhang:
Learning Linear Dynamical Systems via Spectral Filtering. NIPS 2017: 6702-6712 - [i3]Elad Hazan, Karan Singh, Cyril Zhang:
Efficient Regret Minimization in Non-Convex Games. CoRR abs/1708.00075 (2017) - [i2]Brian Bullins, Cyril Zhang, Yi Zhang:
Not-So-Random Features. CoRR abs/1710.10230 (2017) - [i1]Elad Hazan, Karan Singh, Cyril Zhang:
Learning Linear Dynamical Systems via Spectral Filtering. CoRR abs/1711.00946 (2017)
Coauthor Index
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last updated on 2024-10-08 20:34 CEST by the dblp team
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