Yen, Ian En-Hsu

19 publications

ICLR 2025 MagicDec: Breaking the Latency-Throughput Tradeoff for Long Context Generation with Speculative Decoding Ranajoy Sadhukhan, Jian Chen, Zhuoming Chen, Vashisth Tiwari, Ruihang Lai, Jinyuan Shi, Ian En-Hsu Yen, Avner May, Tianqi Chen, Beidi Chen

ICML 2018 Loss Decomposition for Fast Learning in Large Output Spaces Ian En-Hsu Yen, Satyen Kale, Felix Yu, Daniel Holtmann-Rice, Sanjiv Kumar, Pradeep Ravikumar

NeurIPS 2018 MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization Ian En-Hsu Yen, Wei-Cheng Lee, Kai Zhong, Sung-En Chang, Pradeep K Ravikumar, Shou-De Lin

AISTATS 2018 Random Warping Series: A Random Features Method for Time-Series Embedding Lingfei Wu, Ian En-Hsu Yen, Jinfeng Yi, Fangli Xu, Qi Lei, Michael Witbrock

NeurIPS 2018 Representer Point Selection for Explaining Deep Neural Networks Chih-Kuan Yeh, Joon Kim, Ian En-Hsu Yen, Pradeep K Ravikumar

ICML 2017 Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization Qi Lei, Ian En-Hsu Yen, Chao-yuan Wu, Inderjit S. Dhillon, Pradeep Ravikumar

AISTATS 2017 Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain Xiangru Huang, Ian En-Hsu Yen, Ruohan Zhang, Qixing Huang, Pradeep Ravikumar, Inderjit S. Dhillon

ICML 2017 Latent Feature Lasso Ian En-Hsu Yen, Wei-Cheng Lee, Sung-En Chang, Arun Sai Suggala, Shou-De Lin, Pradeep Ravikumar

AISTATS 2017 Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition Jiong Zhang, Ian En-Hsu Yen, Pradeep Ravikumar, Inderjit S. Dhillon

ICML 2016 A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery Ian En-Hsu Yen, Xin Lin, Jiong Zhang, Pradeep Ravikumar, Inderjit Dhillon

NeurIPS 2016 Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain Ian En-Hsu Yen, Xiangru Huang, Kai Zhong, Ruohan Zhang, Pradeep K Ravikumar, Inderjit S Dhillon

UAI 2016 Large-Scale Submodular Greedy Exemplar Selection with Structured Similarity Matrices Dmitry Malioutov, Abhishek Kumar, Ian En-Hsu Yen

ICML 2016 PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification Ian En-Hsu Yen, Xiangru Huang, Pradeep Ravikumar, Kai Zhong, Inderjit Dhillon

AISTATS 2016 Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation Ian En-Hsu Yen, Dmitry Malioutov, Abhishek Kumar

NeurIPS 2015 A Dual Augmented Block Minimization Framework for Learning with Limited Memory Ian En-Hsu Yen, Shan-Wei Lin, Shou-De Lin

NeurIPS 2015 Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent Ian En-Hsu Yen, Kai Zhong, Cho-Jui Hsieh, Pradeep K Ravikumar, Inderjit S Dhillon

NeurIPS 2014 Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods Under High-Dimensional Settings Ian En-Hsu Yen, Cho-Jui Hsieh, Pradeep K Ravikumar, Inderjit S Dhillon

NeurIPS 2014 Proximal Quasi-Newton for Computationally Intensive L1-Regularized M-Estimators Kai Zhong, Ian En-Hsu Yen, Inderjit S Dhillon, Pradeep K Ravikumar

NeurIPS 2014 Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space Ian En-Hsu Yen, Ting-Wei Lin, Shou-De Lin, Pradeep K Ravikumar, Inderjit S Dhillon