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Koby Crammer

48 papers · 2001–2022 · 12 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (23) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (12) πŸƒ Academic Marathon (21) 🐝 Cross-Pollinator (14) 🌟 Keyword Trendsetter Combo (7) πŸ”¬ Deep Specialist (10) πŸ† Keyword Champion 🌱 Topic Pioneer πŸš€ Conference Pioneer πŸ’Ž Century Club (48) ❓ The Questioner (2) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (82) πŸ”₯ Unstoppable (6) ⚑ Prolific Year (5)

Conferences

NIPS (13) JMLR (8) AISTATS (7) EMNLP (5) ACL (4) NAACL (3) ICML (2) IJCAI (2) ACML (1) COLING (1) COLT (1) ICLR (1)

Top co-authors

Fernando Pereira (7) Mark Dredze (7) Edward Moroshko (4) Alex Kulesza (4) Yoram Singer (4) Jennifer Wortman (3) Shie Mannor (3) Avihai Mejer (3) Peter Bartlett (2) Yevgeny Seldin (2)

Keywords

online learning (18) multi-armed bandit (5) binary classification (5) regret bound (5) domain adaptation (5) support vector machine (4) transfer learning (4) mistake bound (4) adversarial learning (3) confidence-weighted learning (3) multiclass classification (3) multi-task learning (3) sentiment classification (3) convex optimization (3) multi-source learning (2) stochastic gradient descent (2) active learning (2) margin maximization (2) margin-based learning (2) classification (2)

Papers

Weighted Training for Cross-Task Learning ICLR 2022
Efficient Loss-Based Decoding on Graphs for Extreme Classification NIPS 2018
Rotting Bandits NIPS 2017
Convex Multi-Task Learning by Clustering AISTATS 2015
Linear Multi-Resource Allocation with Semi-Bandit Feedback NIPS 2015
Second-Order Non-Stationary Online Learning for Regression JMLR 2015
Robust Forward Algorithms via PAC-Bayes and Laplace Distributions AISTATS 2014
Prediction with Limited Advice and Multiarmed Bandits with Paid Observations ICML 2014
Concept Drift Detection Through Resampling ICML 2014
Doubly Aggressive Selective Sampling Algorithms for Classification AISTATS 2014
Selective Sampling with Drift AISTATS 2014
Learning Multiple Tasks in Parallel with a Shared Annotator NIPS 2014
Multi Class Learning with Individual Sparsity IJCAI 2013
Open Problem: Adversarial Multiarmed Bandits with Limited Advice COLT 2013
A Last-Step Regression Algorithm for Non-Stationary Online Learning AISTATS 2013
Hartigan’s K-Means Versus Lloyd’s K-Means β€” Is It Time for a Change? IJCAI 2013
Are You Sure? Confidence in Prediction of Dependency Tree Edges NAACL 2012
Volume Regularization for Binary Classification NIPS 2012
Learning Multiple Tasks using Shared Hypotheses NIPS 2012
Confidence-Weighted Linear Classification for Text Categorization JMLR 2012
Metric Learning for Graph-Based Domain Adaptation COLING 2012
More Is Better: Large Scale Partially-supervised Sentiment Classification ACML 2012
A Simple Geometric Interpretation of SVM using Stochastic Adversaries AISTATS 2012
Breaking the Curse of Kernelization: Budgeted Stochastic Gradient Descent for Large-Scale SVM Training JMLR 2012
Training Dependency Parser Using Light Feedback NAACL 2012
Exploiting Feature Covariance in High-Dimensional Online Learning AISTATS 2010
New Adaptive Algorithms for Online Classification NIPS 2010
Learning via Gaussian Herding NIPS 2010
Learning Better Data Representation Using Inference-Driven Metric Learning ACL 2010
Confidence in Structured-Prediction Using Confidence-Weighted Models EMNLP 2010
Adaptive Regularization of Weight Vectors NIPS 2009
Multi-Class Confidence Weighted Algorithms EMNLP 2009
Loss-Sensitive Discriminative Training of Machine Transliteration Models NAACL 2009
Active Learning with Confidence ACL 2008
Online Methods for Multi-Domain Learning and Adaptation EMNLP 2008
One-Class Clustering in the Text Domain EMNLP 2008
Advanced Online Learning for Natural Language Processing ACL 2008
Learning from Multiple Sources JMLR 2008
Exact Convex Confidence-Weighted Learning NIPS 2008
Learning Bounds for Domain Adaptation NIPS 2007
Online Passive-Aggressive Algorithms JMLR 2006
Learning from Multiple Sources NIPS 2006
Analysis of Representations for Domain Adaptation NIPS 2006
Flexible Text Segmentation with Structured Multilabel Classification EMNLP 2005
Online Large-Margin Training of Dependency Parsers ACL 2005
Ultraconservative Online Algorithms for Multiclass Problems JMLR 2003
A Family of Additive Online Algorithms for Category Ranking JMLR 2003
On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines JMLR 2001