Xingyou Song

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 42

Top Topics

Reinforcement Learning

Top Venues

Publications

Xingyou Song, Oscar Li, Chansoo Lee, Bangding Yang, Daiyi Peng, Sagi Perel, Yutian Chen
OmniPred: Language Models as Universal Regressors. CoRR (2024)
Xingyou Song, Yingtao Tian, Robert Tjarko Lange, Chansoo Lee, Yujin Tang, Yutian Chen
Position: Leverage Foundational Models for Black-Box Optimization. CoRR (2024)
Stephen Kelly, Daniel S. Park, Xingyou Song, Mitchell McIntire, Pranav Nashikkar, Ritam Guha, Wolfgang Banzhaf, Kalyanmoy Deb, Vishnu Naresh Boddeti, Jie Tan, Esteban Real
Discovering Adaptable Symbolic Algorithms from Scratch. IROS (2023)
Tamás Sarlós, Xingyou Song, David P. Woodruff, Qiuyi Zhang
Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products. CoRR (2023)
Stephen Kelly, Daniel S. Park, Xingyou Song, Mitchell McIntire, Pranav Nashikkar, Ritam Guha, Wolfgang Banzhaf, Kalyanmoy Deb, Vishnu Naresh Boddeti, Jie Tan, Esteban Real
Discovering Adaptable Symbolic Algorithms from Scratch. CoRR (2023)
Tamás Sarlós, Xingyou Song, David P. Woodruff, Richard Zhang
Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products. NeurIPS (2023)
Yingjie Miao, Xingyou Song, John D. Co-Reyes, Daiyi Peng, Summer Yue, Eugene Brevdo, Aleksandra Faust
Differentiable Architecture Search for Reinforcement Learning. AutoML (2022)
Xingyou Song, Sagi Perel, Chansoo Lee, Greg Kochanski, Daniel Golovin
Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization. AutoML (2022)
Jack Parker-Holder, Raghu Rajan, Xingyou Song, André Biedenkapp, Yingjie Miao, Theresa Eimer, Baohe Zhang, Vu Nguyen, Roberto Calandra, Aleksandra Faust, Frank Hutter, Marius Lindauer
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems. CoRR (2022)
Xingyou Song, Sagi Perel, Chansoo Lee, Greg Kochanski, Daniel Golovin
Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization. CoRR (2022)
Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Qiuyi Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas
Towards Learning Universal Hyperparameter Optimizers with Transformers. CoRR (2022)
Jack Parker-Holder, Raghu Rajan, Xingyou Song, André Biedenkapp, Yingjie Miao, Theresa Eimer, Baohe Zhang, Vu Nguyen, Roberto Calandra, Aleksandra Faust, Frank Hutter, Marius Lindauer
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems. J. Artif. Intell. Res. 74 (2022)
Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Richard Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas
Towards Learning Universal Hyperparameter Optimizers with Transformers. NeurIPS (2022)
Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Davis, Adrian Weller
Debiasing a First-order Heuristic for Approximate Bi-level Optimization. CoRR (2021)
Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Daiyi Peng, Deepali Jain, Wenbo Gao, Aldo Pacchiano, Tamás Sarlós, Yuxiang Yang
ES-ENAS: Combining Evolution Strategies with Neural Architecture Search at No Extra Cost for Reinforcement Learning. CoRR (2021)
Krzysztof Marcin Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamás Sarlós, Peter Hawkins, Jared Quincy Davis, Afroz Mohiuddin, Lukasz Kaiser, David Benjamin Belanger, Lucy J. Colwell, Adrian Weller
Rethinking Attention with Performers. ICLR (2021)
Yingjie Miao, Xingyou Song, Daiyi Peng, Summer Yue, Eugene Brevdo, Aleksandra Faust
RL-DARTS: Differentiable Architecture Search for Reinforcement Learning. CoRR (2021)
Valerii Likhosherstov, Krzysztof Marcin Choromanski, Jared Quincy Davis, Xingyou Song, Adrian Weller
Sub-Linear Memory: How to Make Performers SLiM. NeurIPS (2021)
Krzysztof Choromanski, Deepali Jain, Jack Parker-Holder, Xingyou Song, Valerii Likhosherstov, Anirban Santara, Aldo Pacchiano, Yunhao Tang, Adrian Weller
Unlocking Pixels for Reinforcement Learning via Implicit Attention. CoRR (2021)
Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Quincy Davis, Adrian Weller
Debiasing a First-order Heuristic for Approximate Bi-level Optimization. ICML (2021)
Xingyou Song, Wenbo Gao, Yuxiang Yang, Krzysztof Choromanski, Aldo Pacchiano, Yunhao Tang
ES-MAML: Simple Hessian-Free Meta Learning. ICLR (2020)
Daniel Golovin, John Karro, Greg Kochanski, Chansoo Lee, Xingyou Song, Qiuyi Zhang
Gradientless Descent: High-Dimensional Zeroth-Order Optimization. ICLR (2020)
Valerii Likhosherstov, Krzysztof Choromanski, Jared Davis, Xingyou Song, Adrian Weller
Sub-Linear Memory: How to Make Performers SLiM. CoRR (2020)
Xingyou Song, Yuxiang Yang, Krzysztof Choromanski, Ken Caluwaerts, Wenbo Gao, Chelsea Finn, Jie Tan
Rapidly Adaptable Legged Robots via Evolutionary Meta-Learning. CoRR (2020)
Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Davis, Adrian Weller
UFO-BLO: Unbiased First-Order Bilevel Optimization. CoRR (2020)
Xingyou Song, Yuxiang Yang, Krzysztof Choromanski, Ken Caluwaerts, Wenbo Gao, Chelsea Finn, Jie Tan
Rapidly Adaptable Legged Robots via Evolutionary Meta-Learning. IROS (2020)
Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamás Sarlós, Adrian Weller, Vikas Sindhwani
Stochastic Flows and Geometric Optimization on the Orthogonal Group. ICML (2020)
Wenbo Gao, Laura Graesser, Krzysztof Choromanski, Xingyou Song, Nevena Lazic, Pannag Sanketi, Vikas Sindhwani, Navdeep Jaitly
Robotic Table Tennis with Model-Free Reinforcement Learning. IROS (2020)
Wenbo Gao, Laura Graesser, Krzysztof Choromanski, Xingyou Song, Nevena Lazic, Pannag Sanketi, Vikas Sindhwani, Navdeep Jaitly
Robotic Table Tennis with Model-Free Reinforcement Learning. CoRR (2020)
Krzysztof Marcin Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani
Ode to an ODE. NeurIPS (2020)
Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamás Sarlós, Adrian Weller, Vikas Sindhwani
Stochastic Flows and Geometric Optimization on the Orthogonal Group. CoRR (2020)
Krzysztof Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani
An Ode to an ODE. CoRR (2020)
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Jared Davis, Tamás Sarlós, David Belanger, Lucy J. Colwell, Adrian Weller
Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers. CoRR (2020)
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamás Sarlós, Peter Hawkins, Jared Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy J. Colwell, Adrian Weller
Rethinking Attention with Performers. CoRR (2020)
Xingyou Song, Yiding Jiang, Stephen Tu, Yilun Du, Behnam Neyshabur
Observational Overfitting in Reinforcement Learning. ICLR (2020)
Alex Irpan, Xingyou Song
The Principle of Unchanged Optimality in Reinforcement Learning Generalization. CoRR (2019)
Xingyou Song, Wenbo Gao, Yuxiang Yang, Krzysztof Choromanski, Aldo Pacchiano, Yunhao Tang
ES-MAML: Simple Hessian-Free Meta Learning. CoRR (2019)
Xingyou Song, Yiding Jiang, Stephen Tu, Yilun Du, Behnam Neyshabur
Observational Overfitting in Reinforcement Learning. CoRR (2019)
Xingyou Song, Yilun Du, Jacob Jackson
An Empirical Study on Hyperparameters and their Interdependence for RL Generalization. CoRR (2019)
Daniel Golovin, John Karro, Greg Kochanski, Chansoo Lee, Xingyou Song, Qiuyi Zhang
Gradientless Descent: High-Dimensional Zeroth-Order Optimization. CoRR (2019)
Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Wenbo Gao, Aldo Pacchiano, Tamás Sarlós, Deepali Jain, Yuxiang Yang
Reinforcement Learning with Chromatic Networks. CoRR (2019)
Jordan Prosky, Xingyou Song, Andrew Tan, Michael Zhao
Sentiment Predictability for Stocks. CoRR (2017)