Scholar
Chang Deng
Google Scholar ID: 51voxF8AAAAJ
University of Chicago
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Machine Learning
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changdeng@uchicago.edu
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Publications
1 items
Differentiable Structure Learning for General Binary Data
2025
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Resume (English only)
Academic Achievements
NeurIPS 2025: "Differentiable Structure Learning for General Binary Data" (first author)
NeurIPS 2024: "Markov Equivalence and Consistency in Differentiable Structure Learning" (first author)
Naval Research Logistics 2024: "Data-driven Forecasting and Reference Prices with Exposure Effect" (co-author)
Statistics and Computing 2024: "High-dimensional sparse single–index regression via Hilbert–Schmidt independence criterion" (co-author)
NeurIPS 2023: "Global Optimality in Bivariate Gradient-based DAG Learning" (first author)
ICML 2023: "Optimizing NOTEARS objective via topological swaps" (first author)
IEEE Big Data 2021: "A simple approach to balance task loss in multi-task learning" (co-author)
ECML PKDD 2021: "Deep multi-task augmented feature learning via hierarchical graph neural network" (co-author)
Developed and maintains Dagrad, a Python package for differentiable (gradient-based) structure learning methods
Serves as reviewer for top conferences: NeurIPS (2024–2025), ICLR (2025), AISTATS (2025), CLeaR (2025), ICML (2025), UAI (2025), AAAI (2026), TMLR
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