Ian En-Hsu Yen

20 papers · 2014–2025 · 6 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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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Half 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (35)

🏆 Keyword Champion (4) 🗃️ Keyword Collector (102) 💎 Century Club · Bronze 🔥 Unstoppable · Bronze ⚡ Prolific Year · Productive

Venues

NeurIPS (8) ICML (5) AISTATS (4) EMNLP (1) ICLR (1) NAACL (1)

Top co-authors

Pradeep Ravikumar (8) Pradeep K Ravikumar (7) Kai Zhong (5) Inderjit S Dhillon (5) Inderjit Dhillon (4) Shou-De Lin (4) Xiangru Huang (3) Wei-Cheng Lee (2) Ruohan Zhang (2) Lingfei Wu (2)

Research topics

Machine Learning (16) Mathematics & Optimization (13) Core Methods (13) Optimization (13) Optimization & Theory · Machine Learning (9) Artificial Intelligence (4) Core AI (4) Application Areas (3) Deep Learning (2) Bayesian & Probabilistic (2) Learning Types · Machine Learning (2) Natural Language Processing (1) Applications (1) Learning Types · Deep Learning (1) Optimization & Theory · Deep Learning (1)

Keywords

augmented lagrangian (4) convex optimization (4) coordinate descent (3) sparse optimization (3) dual decomposition (2) active set (2) atomic norm regularization (2) support vector machine (2) sparse regression (2) block coordinate descent (2) sparse learning (2) multiple sequence alignment (2) primal-dual optimization (2) multi-label classification (2) empirical risk minimization (2) multi-class classification (2) structured prediction (2) l1 regularization (2) random feature (2) kernel methods (2)

Papers

MagicDec: Breaking the Latency-Throughput Tradeoff for Long Context Generation with Speculative Decoding ICLR 2025 Rethinking Network Pruning – under the Pre-train and Fine-tune Paradigm NAACL 2021 Loss Decomposition for Fast Learning in Large Output Spaces ICML 2018 MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization NeurIPS 2018 Random Warping Series: A Random Features Method for Time-Series Embedding AISTATS 2018 Representer Point Selection for Explaining Deep Neural Networks NeurIPS 2018 Word Mover’s Embedding: From Word2Vec to Document Embedding EMNLP 2018 Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization ICML 2017 Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain AISTATS 2017 Latent Feature Lasso ICML 2017 Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition AISTATS 2017 A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery ICML 2016 Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain NeurIPS 2016 PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification ICML 2016 Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation AISTATS 2016 A Dual Augmented Block Minimization Framework for Learning with Limited Memory NeurIPS 2015 Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent NeurIPS 2015 Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings NeurIPS 2014 Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators NeurIPS 2014 Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space NeurIPS 2014