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Xiangyu Chang

15 papers · 2017–2026 · 8 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+6 more ↓ πŸ—ΊοΈ Taxonomy Completionist (39) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Sprint πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
πŸ† Grand Slam πŸ† Keyword Champion πŸ—ƒοΈ Keyword Collector (92) πŸ“ˆ Trend Setter πŸ’Ž Century Club Β· Bronze πŸ”₯ Unstoppable Β· Bronze

Venues

AAAI (3) ICML (3) JMLR (3) NeurIPS (2) AISTATS (1) COLT (1) CVPR (1) ICLR (1)

Top co-authors

Samet Oymak (5) Haishan Ye (5) Guang Dai (4) Amit Roy-Chowdhury (3) Ivor Tsang (3) Hao Di (3) Yinghui Huang (2) Sk Miraj Ahmed (2) Yingcong Li (2) Fahim Faisal Niloy (2)

Research topics

Machine Learning (12) Optimization & Theory (8) Application Areas (7) Artificial Intelligence (5) Mathematics & Optimization (4) Core Methods (4) Learning Types Β· Machine Learning (4) Deep Learning (3) Core AI (3) Learning Paradigms (3) Optimization (3) Learning Types Β· Deep Learning (2) Data Science & Analytics (1) Natural Language Processing (1) Applications (1)

Keywords

composite optimization (2) transformer architecture (1) few-shot learning (1) double descent (1) stochastic gradient descent (1) semi-supervised learning (1) continual learning (1) spectral clustering (1) domain adaptation (1) sparse learning (1) attention mechanism (1) in-context learning (1) language modeling (1) federated learning (1) communication complexity (1) distributed learning (1) feature correlation (1) decentralized optimization (1) data valuation (1) model compression (1)

Papers

Bayes-Optimal Fair Classification with Multiple Sensitive Features AAAI 2026 Privacy Leaks by Adversaries: Adversarial Iterations for Membership Inference Attack AAAI 2026 AdMiT: Adaptive Multi-Source Tuning in Dynamic Environments CVPR 2025 Optimal Decentralized Composite Optimization for Strongly Convex Functions JMLR 2025 ProAdvPrompter: A Two-Stage Journey to Effective Adversarial Prompting for LLMs ICLR 2025 Provable Benefits of Task-Specific Prompts for In-context Learning AISTATS 2025 CONTRAST: Continual Multi-source Adaptation to Dynamic Distributions NeurIPS 2024 Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods ICML 2024 Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient ICML 2024 Selective Attention: Enhancing Transformer through Principled Context Control NeurIPS 2024 2D-Shapley: A Framework for Fragmented Data Valuation ICML 2023 Randomized Spectral Co-Clustering for Large-Scale Directed Networks JMLR 2023 Statistical Estimation and Online Inference via Local SGD COLT 2022 Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks AAAI 2021 Distributed Semi-supervised Learning with Kernel Ridge Regression JMLR 2017