2026 Yoram Singer: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	75	1366	1323	712	686	162	65434

Research.com Recognitions

2010 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to the theory and practice of efficient machine learning algorithms.

Overview

Yoram Singer is affiliated with Princeton University in the United States, specializing in computer science with a focus on artificial intelligence and computational theory.

Their research spans several subfields within computer science, including:

Artificial Intelligence
Computational Theory and Mathematics
Numerical Analysis
Computer Graphics and Computer-Aided Design
Information Systems

Their main research topics involve:

Complexity and Algorithms in Graphs
Adversarial Robustness in Machine Learning
Stochastic Gradient Optimization Techniques
Machine Learning and Algorithms
Topic Modeling
Mathematical Approximation and Integration
Computational Geometry and Mesh Generation

Yoram Singer has a substantial publication record, including papers in the following venues:

arXiv (Cornell University) - 9 publications
Operations Research - 1 publication
Journal of the ACM - 1 publication

Selected recent papers include:

"Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Bias," 2020, arXiv (Cornell University)
"Maximization of Approximately Submodular Functions," 2024, arXiv (Cornell University)
"Tree of Attacks: Jailbreaking Black-Box LLMs Automatically," 2023, arXiv (Cornell University)
"An Optimal Approximation for Submodular Maximization Under a Matroid Constraint in the Adaptive Complexity Model," 2021, Operations Research
"An Optimal Elimination Algorithm for Learning a Best Arm," 2020, arXiv (Cornell University)

Frequent co-authors of Yoram Singer include:

Eric Balkanski
Sharon Qian
Paul Kassianik
Amin Karbasi
Aviad Rubinstein

Yoram Singer received recognition as a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 2010 for contributions to the theory and practice of efficient machine learning algorithms.

Best Publications

Adaptive Subgradient Methods for Online Learning and Stochastic Optimization

John Duchi;Elad Hazan;Yoram Singer

11729
Citations
Improved boosting algorithms using confidence-rated predictions

Robert E. Schapire;Yoram Singer

4580
Citations
Feature-rich part-of-speech tagging with a cyclic dependency network

Kristina Toutanova;Dan Klein;Christopher D. Manning;Yoram Singer

4339
Citations
BoosTexter: A Boosting-based Systemfor Text Categorization

Robert E. Schapire;Yoram Singer

3226
Citations
An efficient boosting algorithm for combining preferences

Yoav Freund;Raj Iyer;Robert E. Schapire;Yoram Singer

3027
Citations
On the algorithmic implementation of multiclass kernel-based vector machines

Koby Crammer;Yoram Singer

2804
Citations
Reducing multiclass to binary: a unifying approach for margin classifiers

Erin L. Allwein;Robert E. Schapire;Yoram Singer

2753
Citations
Pegasos: primal estimated sub-gradient solver for SVM

Shai Shalev-Shwartz;Yoram Singer;Nathan Srebro;Andrew Cotter

2730
Citations
Online Passive-Aggressive Algorithms

Koby Crammer;Koby Crammer;Ofer Dekel;Joseph Keshet;Shai Shalev-Shwartz

2225
Citations
Efficient projections onto the l1-ball for learning in high dimensions

John Duchi;Shai Shalev-Shwartz;Yoram Singer;Tushar Chandra

1576
Citations
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM

Shai Shalev-Shwartz;Yoram Singer;Nathan Srebro

1557
Citations
The Hierarchical Hidden Markov Model: Analysis and Applications

Shai Fine;Yoram Singer;Naftali Tishby

1410
Citations
Context-sensitive learning methods for text categorization

William W. Cohen;Yoram Singer

1322
Citations
Unsupervised Models for Named Entity Classification

Michael Collins;Yoram Singer

1304
Citations
On the Learnability and Design of Output Codes for Multiclass Problems

Koby Crammer;Yoram Singer

1016
Citations
Logistic Regression, AdaBoost and Bregman Distances

Michael Collins;Robert E. Schapire;Yoram Singer

1010
Citations
Zero-Shot Learning by Convex Combination of Semantic Embeddings

Mohammad Norouzi;Tomas Mikolov;Samy Bengio;Yoram Singer

904
Citations
Train faster, generalize better: stability of stochastic gradient descent

Moritz Hardt;Benjamin Recht;Yoram Singer

889
Citations
Learning to order things

William W. Cohen;Robert E. Schapire;Yoram Singer

865
Citations
Pranking with Ranking

Koby Crammer;Yoram Singer

861
Citations
Ordered landmarks in planning

Jörg Hoffmann;Julie Porteous;Laura Sebastia

430
Citations

Frequent Co-Authors

Shai Shalev-Shwartz Hebrew University of Jerusalem

Ofer Dekel Microsoft (United States)

Robert E. Schapire Microsoft (United States)

Koby Crammer Technion – Israel Institute of Technology

Samy Bengio Apple (United States)

Naftali Tishby Hebrew University of Jerusalem

William W. Cohen Carnegie Mellon University

Tushar Deepak Chandra Google (United States)

John C. Duchi Stanford University

Manfred K. Warmuth Google (United States)

External Links

Personal website of Yoram Singer Google Scholar page

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