Scholar
Yiding Jiang
Google Scholar ID: x9qzWg8AAAAJ
Carnegie Mellon University
Citations & Impact
Citations
2,302
H-index
15
i10-index
17
Publications
20
Co-authors
16
list available
Publications
Resume (English only)
Academic Achievements
- - Publications:
- * Training a Generally Curious Agent (ICML, 2025)
- * Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws (ICLR, 2025)
- * On the Joint Interaction of Models, Data, and Features (ICLR, 2024)
- * On the Importance of Exploration for Generalization in Reinforcement Learning (NeurIPS, 2023)
- * Learning Options via Compression (NeurIPS, 2022)
- * Assessing Generalization of SGD via Disagreement (ICLR, 2022)
- * Fantastic Generalization Measures and Where to Find Them (ICLR, 2020)
- * Language as an Abstraction for Hierarchical Deep Reinforcement Learning (NeurIPS, 2019)
- - Awards: Supported by the Google PhD Fellowship
Research Experience
- - AI Resident: Google Research
- - Research Intern: Meta AI Research and Cerebras Systems
- - Teaching Assistant: 10-708 Probabilistic Graphical Models, Carnegie Mellon University (Fall 2022)
- - Teaching Assistant: 10-725 Convex Optimization, Carnegie Mellon University (Fall 2021)
- - Reader: CS170 Efficient Algorithms and Intractable Problems, UC Berkeley (Fall 2017)
Education
- - PhD: Carnegie Mellon University, Machine Learning Department, Advisor: Professor Zico Kolter
- - B.S.: UC Berkeley, Electrical Engineering and Computer Science, Advisor: Professor Ken Goldberg
Background
- - Research Interests: Understanding the science of deep learning and using these insights to improve models. Research areas include representation learning, reinforcement learning, and generalization.
- - Professional Field: Machine Learning
- - Brief Introduction: PhD student at the Machine Learning Department of Carnegie Mellon University, working with Professor Zico Kolter.
Miscellany
- - Personal Interests: Not provided
