Xingyou Song

According to our database, Xingyou Song authored at least 30 papers between 2017 and 2024.

Collaborative distances:

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

2024

Predicting from Strings: Language Model Embeddings for Bayesian Optimization.

Tung Nguyen, Qiuyi Zhang, Bangding Yang, Chansoo Lee, Jorg Bornschein, Yingjie Miao, Sagi Perel, Yutian Chen, Xingyou Song

CoRR, 2024

The Vizier Gaussian Process Bandit Algorithm.

Xingyou Song, Qiuyi Zhang, Chansoo Lee, Emily Fertig, Tzu-Kuo Huang, Lior Belenki, Greg Kochanski, Setareh Ariafar, Srinivas Vasudevan, Sagi Perel, Daniel Golovin

CoRR, 2024

OmniPred: Language Models as Universal Regressors.

Xingyou Song, Oscar Li, Chansoo Lee, Bangding Yang, Daiyi Peng, Sagi Perel, Yutian Chen

CoRR, 2024

Position: Leverage Foundational Models for Black-Box Optimization.

Xingyou Song, Yingtao Tian, Robert Tjarko Lange, Chansoo Lee, Yujin Tang, Yutian Chen

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products.

Tamás Sarlós, Xingyou Song, David P. Woodruff, Richard Zhang

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

Discovering Adaptable Symbolic Algorithms from Scratch.

Stephen Kelly, Daniel S. Park, Xingyou Song, Mitchell McIntire, Pranav Nashikkar, Ritam Guha, Wolfgang Banzhaf, Kalyanmoy Deb, Vishnu Naresh Boddeti, Jie Tan, Esteban Real

IROS, 2023

2022

Automated Reinforcement Learning (AutoRL): A Survey and Open Problems.

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

J. Artif. Intell. Res., 2022

Towards Learning Universal Hyperparameter Optimizers with Transformers.

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

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

Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization.

Xingyou Song, Sagi Perel, Chansoo Lee, Greg Kochanski, Daniel Golovin

Proceedings of the International Conference on Automated Machine Learning, 2022

Differentiable Architecture Search for Reinforcement Learning.

Yingjie Miao, Xingyou Song, John D. Co-Reyes, Daiyi Peng, Summer Yue, Eugene Brevdo, Aleksandra Faust

Proceedings of the International Conference on Automated Machine Learning, 2022

2021

RL-DARTS: Differentiable Architecture Search for Reinforcement Learning.

Yingjie Miao, Xingyou Song, Daiyi Peng, Summer Yue, Eugene Brevdo, Aleksandra Faust

CoRR, 2021

Unlocking Pixels for Reinforcement Learning via Implicit Attention.

Krzysztof Choromanski, Deepali Jain, Jack Parker-Holder, Xingyou Song, Valerii Likhosherstov, Anirban Santara, Aldo Pacchiano, Yunhao Tang, Adrian Weller

CoRR, 2021

ES-ENAS: Combining Evolution Strategies with Neural Architecture Search at No Extra Cost for Reinforcement Learning.

Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Daiyi Peng, Deepali Jain, Wenbo Gao, Aldo Pacchiano, Tamás Sarlós, Yuxiang Yang

CoRR, 2021

Sub-Linear Memory: How to Make Performers SLiM.

Valerii Likhosherstov, Krzysztof Marcin Choromanski, Jared Quincy Davis, Xingyou Song, Adrian Weller

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Debiasing a First-order Heuristic for Approximate Bi-level Optimization.

Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Quincy Davis, Adrian Weller

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

Rethinking Attention with Performers.

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

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

An Ode to an ODE.

Krzysztof Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani

CoRR, 2020

UFO-BLO: Unbiased First-Order Bilevel Optimization.

Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Davis, Adrian Weller

CoRR, 2020

Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers.

Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Jared Davis, Tamás Sarlós, David Belanger, Lucy J. Colwell, Adrian Weller

CoRR, 2020

Ode to an ODE.

Krzysztof Marcin Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani

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

Rapidly Adaptable Legged Robots via Evolutionary Meta-Learning.

Xingyou Song, Yuxiang Yang, Krzysztof Choromanski, Ken Caluwaerts, Wenbo Gao, Chelsea Finn, Jie Tan

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Robotic Table Tennis with Model-Free Reinforcement Learning.

Wenbo Gao, Laura Graesser, Krzysztof Choromanski, Xingyou Song, Nevena Lazic, Pannag Sanketi, Vikas Sindhwani, Navdeep Jaitly

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Stochastic Flows and Geometric Optimization on the Orthogonal Group.

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

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

Observational Overfitting in Reinforcement Learning.

Xingyou Song, Yiding Jiang, Stephen Tu, Yilun Du, Behnam Neyshabur

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

ES-MAML: Simple Hessian-Free Meta Learning.

Xingyou Song, Wenbo Gao, Yuxiang Yang, Krzysztof Choromanski, Aldo Pacchiano, Yunhao Tang

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

Gradientless Descent: High-Dimensional Zeroth-Order Optimization.

Daniel Golovin, John Karro, Greg Kochanski, Chansoo Lee, Xingyou Song, Qiuyi (Richard) Zhang

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

2019

Reinforcement Learning with Chromatic Networks.

Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Wenbo Gao, Aldo Pacchiano, Tamás Sarlós, Deepali Jain, Yuxiang Yang

CoRR, 2019

An Empirical Study on Hyperparameters and their Interdependence for RL Generalization.

Xingyou Song, Yilun Du, Jacob Jackson

CoRR, 2019

The Principle of Unchanged Optimality in Reinforcement Learning Generalization.

Alex Irpan, Xingyou Song

CoRR, 2019

2017

Sentiment Predictability for Stocks.

Jordan Prosky, Xingyou Song, Andrew Tan, Michael Zhao

CoRR, 2017