Adam Tauman Kalai | Academic Influence

Adam Tauman Kalai's AcademicInfluence.com Rankings

Adam Tauman Kalai

Computer Science

#3621

World Rank

#3804

Historical Rank

Machine Learning

#1058

World Rank

#1074

Historical Rank

Artificial Intelligence

#5464

World Rank

#5539

Historical Rank

Database

#8112

World Rank

#8459

Historical Rank

computer-science Degrees

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Computer Science

Adam Tauman Kalai's Degrees

PhD Computer Science University of Chicago
Bachelors Mathematics University of Chicago

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Why Is Adam Tauman Kalai Influential?

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According to Wikipedia, Adam Tauman Kalai is an American computer scientist who specializes in Machine Learning and works as a Senior Principal Researcher at Microsoft Research New England. Education and career Kalai graduated from Harvard University in 1996 and received a PhD from Carnegie Mellon University in 2001, where he worked under doctoral advisor Avrim Blum. He did his postdoctoral study at the Massachusetts Institute of Technology before becoming a faculty member at the Toyota Technological Institute at Chicago and then the Georgia Institute of Technology. He joined Microsoft Research in 2008.

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Adam Tauman Kalai's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016) (2027)
Efficient algorithms for online decision problems (2005) (705)
Online convex optimization in the bandit setting: gradient descent without a gradient (2004) (695)
Noise-tolerant learning, the parity problem, and the statistical query model (2000) (651)
Beating the hold-out: bounds for K-fold and progressive cross-validation (1999) (314)
Agnostically learning halfspaces (2005) (294)
Analysis of Perceptron-Based Active Learning (2009) (271)
Adaptively Learning the Crowd Kernel (2011) (251)
Trust-based recommendation systems: an axiomatic approach (2008) (243)
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting (2019) (234)
Efficiently learning mixtures of two Gaussians (2010) (205)
Universal Portfolios With and Without Transaction Costs (1997) (205)
Decoupled Classifiers for Group-Fair and Efficient Machine Learning (2017) (203)
Efficient algorithms for universal portfolios (2000) (174)
Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression (2011) (152)
A Machine Learning Framework for Programming by Example (2013) (147)
Simulated Annealing for Convex Optimization (2006) (144)
The Isotron Algorithm: High-Dimensional Isotonic Regression (2009) (116)
A Note on Learning from Multiple-Instance Examples (2004) (106)
Playing games with approximation algorithms (2007) (100)
Omnivergent Stereo (2002) (98)
The myth of the folk theorem (2008) (92)
A commitment folk theorem (2010) (87)
Boosting in the presence of noise (2003) (81)
What are the Biases in My Word Embedding? (2018) (79)
Dueling algorithms (2011) (63)
Static Optimality and Dynamic Search-Optimality in Lists and Trees (2002) (61)
Agnostically learning decision trees (2008) (61)
Disentangling Gaussians (2012) (60)
Finely-competitive paging (1999) (57)
What’s in a Name? Reducing Bias in Bios without Access to Protected Attributes (2019) (57)
Cooperation in Strategic Games Revisited (2013) (56)
Tight asymptotic bounds for the deletion channel with small deletion probabilities (2010) (55)
On agnostic boosting and parity learning (2008) (50)
A colorful approach to text processing by example (2013) (49)
Quantifying and Reducing Stereotypes in Word Embeddings (2016) (49)
The disparate equilibria of algorithmic decision making when individuals invest rationally (2019) (47)
On Suggesting Phrases vs. Predicting Words for Mobile Text Composition (2016) (46)
Learning and Smoothed Analysis (2009) (46)
Potential-Based Agnostic Boosting (2009) (41)
Decoupled classifiers for fair and efficient machine learning (2017) (40)
Graph model selection using maximum likelihood (2006) (40)
Noise-tolerant learning, the parity problem, and the statistical query model (2000) (36)
Reliable Agnostic Learning (2012) (35)
Compression without a common prior: an information-theoretic justification for ambiguity in language (2011) (32)
An Approach to Bounded Rationality (2006) (31)
Efficient pattern-matching with don't cares (2002) (28)
Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons (2015) (28)
OMG UR Funny! Computer-Aided Humor with an Application to Chat (2015) (26)
Unleashing Linear Optimizers for Group-Fair Learning and Optimization (2018) (26)
Geometric algorithms for online optimization (2002) (26)
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples (2020) (25)
Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context (2017) (25)
Supervising Unsupervised Learning (2017) (24)
On-line algorithms for combining language models (1999) (23)
From Batch to Transductive Online Learning (2005) (22)
A Crowd of Your Own: Crowdsourcing for On-Demand Personalization (2014) (21)
Using Large Language Models to Simulate Multiple Humans (2022) (21)
Generating Random Factored Numbers, Easily (2002) (20)
Admission Control to Minimize Rejections (2001) (20)
A Novel Approach to Propagating Distrust (2010) (18)
On the equilibria of alternating move games (2010) (18)
Learning to Prune: Speeding up Repeated Computations (2019) (17)
Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning (2019) (17)
Programming Puzzles (2021) (15)
Strategic Polarization. (2001) (15)
A Query Algorithm for Agnostically Learning DNF? (2008) (13)
ENGINEERING COOPERATION IN TWO-PLAYER GAMES DRAFT SEP 28 , 2009 (2009) (11)
Playing Games without Observing Payoffs (2010) (11)
Learning Monotonic Linear Functions (2004) (11)
A Cooperative Value for Bayesian Games (2010) (11)
Decision trees are PAC-learnable from most product distributions: a smoothed analysis (2008) (11)
Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization (2020) (10)
Online convex optimization in the bandit setting (2005) (9)
Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops (2019) (8)
Feature Multi-Selection among Subjective Features (2013) (7)
Cooperation and competition in strategic games with private information (2010) (7)
Omnipredictors (2021) (7)
Usability of Humanly Computable Passwords (2017) (7)
Reading and Learning Smartfonts (2016) (7)
Designing and Evaluating Livefonts (2017) (7)
Probabilistic and on-line methods in machine learning (2001) (6)
Actively Avoiding Nonsense in Generative Models (2018) (6)
Counterfactual Language Model Adaptation for Suggesting Phrases (2017) (6)
ENGINEERING COOPERATION IN TWO-PLAYER STRATEGIC GAMES DRAFT MARCH 2010 (2010) (5)
Meta-Unsupervised-Learning: A supervised approach to unsupervised learning (2016) (5)
Language Models Can Teach Themselves to Program Better (2022) (5)
Improved rendering of parallax panoramagrams for a time-multiplexed autostereoscopic display (1998) (5)
Personalized Human Computation (2013) (5)
Matching and Grokking: Approaches to Personalized Crowdsourcing (2015) (5)
Cooperation in two person games, revisited (2011) (4)
Efficient Learning with Arbitrary Covariate Shift (2021) (4)
When optimizing nonlinear objectives is no harder than linear objectives (2018) (4)
Learning Nested Halfspaces and Uphill Decision Trees (2007) (4)
Voluntary commitments lead to efficiency (2007) (3)
Algorithmic Greenlining: An Approach to Increase Diversity (2019) (3)
Why GANs are overkill for NLP (2022) (2)
Approximation Algorithms Going Online (2007) (2)
Social Norm Bias: Residual Harms of Fairness-Aware Algorithms (2021) (2)
Efficient Estimators for Generalized Additive Models (2005) (2)
HAI-GEN 2020: Workshop on Human-AI Co-Creation with Generative Models (2020) (1)
ADAPTIVE GENERATION OF PROGRAMMING PUZZLES (2019) (1)
Towards optimally abstaining from prediction with OOD test examples (2021) (1)
Glass-Box Program Synthesis: A Machine Learning Approach (2017) (1)
Towards optimally abstaining from prediction (2021) (1)
Learning to Suggest Phrases (2017) (1)
Hedging Structured Concepts (2010) (0)
Learning Mixtures of Two Gaussians (2010) (0)
Session details: Session 7B (2005) (0)
MUST BE KEPT BLANK ] Personalized Human Computation (2013) (0)
Better Computers for Better People (2016) (0)
DRAFT DO NOT DISTRIBUTE Improved sentence completions in email using context (2016) (0)
Online Learning: Experts and Bandits (2012) (0)
A Uniform Methodology for Ranking Internet Topology Models (2005) (0)
Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms (2022) (0)
A Theory of Unsupervised Translation Motivated by Understanding Animal Communication (2022) (0)
Learning Mixtures of Two Arbitrary Gaussians (2010) (0)
COLT 2010 - The 23rd Conference on Learning Theory, Haifa, Israel, June 27-29, 2010 (2010) (0)
Efficiently Learning Mixtures of Two Arbitrary Gaussians (2010) (0)
Identifying unpredictable test examples with worst-case guarantees (2020) (0)
Textual Features for Programming by Example (2012) (0)
Boosting in the Presence of Noise (Extended Abstract) (2003) (0)
Continuing a Tradition of Excellence (2003) (0)
{13 () Universal Portfolios with and without Transaction Costs (1997) (0)
Schedule at a Glance (2002) (0)
Loss minimization yields multicalibration for large neural networks (2023) (0)
UvA-DARE ( Digital Academic Repository ) Hedging structured concepts (2010) (0)
Partial Matrix Completion (2022) (0)
Are GANs overkill for NLP? (2022) (0)

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