Yoram Singer

32 papers · 2000–2022 · 8 conferences · across top CS/AI conferences

Achievements

+15 more ↓

🧭 Keyword Pioneer 🗺️ Taxonomy Completionist (22) 🌉 Interdisciplinary Bridge 🌈 Renaissance Researcher (5) 🐣 Hot Topic Early Bird

🧭 Keyword Pioneer 🏃 Academic Marathon (22) 🗺️ Taxonomy Completionist (22) 🌟 Keyword Trendsetter Combo (8) 🔬 Deep Specialist (14) 🌱 Topic Pioneer 🏆 Grand Slam 🏆 Keyword Champion 🗃️ Keyword Collector (62) ⚡ Prolific Year (6) 🚀 Conference Pioneer 📈 Trend Setter ❓ The Questioner 💎 Century Club (32) 🔥 Unstoppable (5)

Conferences

JMLR (14) NIPS (8) ICML (4) ICLR (2) AAAI (1) ALT (1) EMNLP (1) NAACL (1)

Top co-authors

Shai Shalev-shwartz (6) Samy Bengio (4) Ofer Dekel (4) Koby Crammer (4) Moritz Hardt (2) Yonatan Amit (2) Chiyuan Zhang (2) John Duchi (2) Vineet Gupta (2) Seungyeon Kim (2)

Keywords

online learning (10) multiclass classification (5) gradient descent (5) text categorization (3) collaborative filtering (3) support vector machine (3) sparse optimization (2) matrix completion (2) empirical loss minimization (2) mistake bound model (2) learning to rank (2) image classification (2) binary classification (2) stochastic gradient descent (2) convex optimization (2) simultaneous projections (2) stochastic optimization (2) multi-task learning (2) metric learning (2) multi-class classification (2)

Papers

Are All Layers Created Equal? JMLR 2022 Exponentiated Gradient Meets Gradient Descent ALT 2020 Proximity Preserving Binary Code Using Signed Graph-Cut AAAI 2020 Identity Crisis: Memorization and Generalization Under Extreme Overparameterization ICLR 2020 Memory Efficient Adaptive Optimization NIPS 2019 Learning a neural response metric for retinal prosthesis ICLR 2018 The Well-Tempered Lasso ICML 2018 Shampoo: Preconditioned Stochastic Tensor Optimization ICML 2018 LLORMA: Local Low-Rank Matrix Approximation JMLR 2016 Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity NIPS 2016 Train faster, generalize better: Stability of stochastic gradient descent ICML 2016 Local Low-Rank Matrix Approximation ICML 2013 Adaptive Subgradient Methods for Online Learning and Stochastic Optimization JMLR 2011 Entire Relaxation Path for Maximum Entropy Problems EMNLP 2011 Efficient Learning using Forward-Backward Splitting NIPS 2009 Group Sparse Coding NIPS 2009 Efficient Online and Batch Learning Using Forward Backward Splitting JMLR 2009 Online Learning of Complex Prediction Problems Using Simultaneous Projections JMLR 2008 Online Learning of Multiple Tasks with a Shared Loss JMLR 2007 Online Classification for Complex Problems Using Simultaneous Projections NIPS 2006 Convex Repeated Games and Fenchel Duality NIPS 2006 Image Retrieval and Classification Using Local Distance Functions NIPS 2006 Support Vector Machines on a Budget NIPS 2006 Online Passive-Aggressive Algorithms JMLR 2006 Efficient Learning of Label Ranking by Soft Projections onto Polyhedra JMLR 2006 Smooth ε-Insensitive Regression by Loss Symmetrization JMLR 2005 An Efficient Boosting Algorithm for Combining Preferences JMLR 2003 A Family of Additive Online Algorithms for Category Ranking JMLR 2003 Ultraconservative Online Algorithms for Multiclass Problems JMLR 2003 Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network NAACL 2003 On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines JMLR 2001 Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers JMLR 2000