Sentiment Predictability for Stocks. - Jordan Prosky; Xingyou Song; Andrew Tan; Michael Zhao (CoRR, 2017)

The Principle of Unchanged Optimality in Reinforcement Learning Generalization. - Alex Irpan; Xingyou Song (CoRR, 2019)

An Empirical Study on Hyperparameters and their Interdependence for RL Generalization. - Xingyou Song; Yilun Du; Jacob Jackson (CoRR, 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 007 (CoRR, 2019)

Gradientless Descent: High-Dimensional Zeroth-Order Optimization. - Daniel Golovin; John Karro; Greg Kochanski; Chansoo Lee; Xingyou Song; Qiuyi (Richard) Zhang (ICLR, 2020)

ES-MAML: Simple Hessian-Free Meta Learning. - Xingyou Song; Wenbo Gao; Yuxiang Yang 007; Krzysztof Choromanski; Aldo Pacchiano; Yunhao Tang (ICLR, 2020)

Observational Overfitting in Reinforcement Learning. - Xingyou Song; Yiding Jiang; Stephen Tu; Yilun Du; Behnam Neyshabur (ICLR, 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 038; Aldo Pacchiano; et al. (ICML, 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 (IROS, 2020)

Rapidly Adaptable Legged Robots via Evolutionary Meta-Learning. - Xingyou Song; Yuxiang Yang 007; Krzysztof Choromanski; Ken Caluwaerts; Wenbo Gao; Chelsea Finn; Jie Tan 001 (IROS, 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 (NeurIPS, 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 002; Lucy J. Colwell; Adrian Weller (CoRR, 2020)

UFO-BLO: Unbiased First-Order Bilevel Optimization. - Valerii Likhosherstov; Xingyou Song; Krzysztof Choromanski; Jared Davis; Adrian Weller (CoRR, 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)

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; et al. (ICLR, 2021)

Debiasing a First-order Heuristic for Approximate Bi-level Optimization. - Valerii Likhosherstov; Xingyou Song; Krzysztof Choromanski; Jared Quincy Davis; Adrian Weller (ICML, 2021)

Sub-Linear Memory: How to Make Performers SLiM. - Valerii Likhosherstov; Krzysztof Marcin Choromanski; Jared Quincy Davis; Xingyou Song; Adrian Weller (NeurIPS, 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 007 (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)

RL-DARTS: Differentiable Architecture Search for Reinforcement Learning. - Yingjie Miao; Xingyou Song; Daiyi Peng; Summer Yue; Eugene Brevdo; Aleksandra Faust (CoRR, 2021)

Differentiable Architecture Search for Reinforcement Learning. - Yingjie Miao; Xingyou Song; John D. Co-Reyes; Daiyi Peng; Summer Yue; Eugene Brevdo; Aleksandra Faust (AutoML, 2022)

Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization. - Xingyou Song; Sagi Perel; Chansoo Lee; Greg Kochanski; Daniel Golovin (AutoML, 2022)

Towards Learning Universal Hyperparameter Optimizers with Transformers. - Yutian Chen 001; Xingyou Song; Chansoo Lee; Zi Wang; Richard Zhang 003; David Dohan; Kazuya Kawakami; Greg Kochanski; Arnaud Doucet; Marc'Aurelio Ranzato; Sagi Perel; Nando de Freitas (NeurIPS, 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)

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 001; Esteban Real (IROS, 2023)

Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products. - Tamás Sarlós; Xingyou Song; David P. Woodruff; Richard Zhang 003 (NeurIPS, 2023)

Position: Leverage Foundational Models for Black-Box Optimization. - Xingyou Song; Yingtao Tian; Robert Tjarko Lange; Chansoo Lee; Yujin Tang; Yutian Chen 001 (ICML, 2024)

The Vizier Gaussian Process Bandit Algorithm. - Xingyou Song; Qiuyi Zhang 001; Chansoo Lee; Emily Fertig; Tzu-Kuo Huang; Lior Belenki; Greg Kochanski; Setareh Ariafar; Srinivas Vasudevan; Sagi Perel; Daniel Golovin (CoRR, 2024)

Predicting from Strings: Language Model Embeddings for Bayesian Optimization. - Tung Nguyen; Qiuyi Zhang 001; Bangding Yang; Chansoo Lee; Jörg Bornschein; Yingjie Miao; Sagi Perel; Yutian Chen 001; Xingyou Song (CoRR, 2024)

OmniPred: Language Models as Universal Regressors. - Xingyou Song; Oscar Li; Chansoo Lee; Bangding Yang; Daiyi Peng; Sagi Perel; Yutian Chen 001 (Trans. Mach. Learn. Res., 2024)

Decoding-based Regression. - Xingyou Song; Dara Bahri (Trans. Mach. Learn. Res., 2025)

Understanding LLM Embeddings for Regression. - Eric Tang; Bangding Yang; Xingyou Song (Trans. Mach. Learn. Res., 2025)

Performance Prediction for Large Systems via Text-to-Text Regression. - Yash Akhauri; Bryan Lewandowski; Cheng-Hsi Lin; Adrian N. Reyes; Grant C. Forbes; Arissa Wongpanich; Bangding Yang; Mohamed S. Abdelfattah; Sagi Perel; Xingyou Song (CoRR, 2025)