What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
Adam Tauman Kalai spends much of his time researching Artificial intelligence, Mathematical optimization, Embedding, Constant and Machine learning.
Adam Tauman Kalai has researched Artificial intelligence in several fields, including Euclidean space and Natural language processing.
His Mathematical optimization research focuses on subjects like Convex set, which are linked to Random coordinate descent, Proximal Gradient Methods, Convex combination and Stochastic gradient descent.
His Embedding research is multidisciplinary, relying on both Word and Programmer.
His work on Transfer of learning, Stability, Active learning and Semi-supervised learning as part of general Machine learning research is frequently linked to Decoupling, bridging the gap between disciplines.
His Discrete mathematics research incorporates themes from Uniform distribution and Combinatorics, Unit sphere.
His most cited work include:
- Man is to computer programmer as woman is to homemaker? debiasing word embeddings (718 citations)
- Online convex optimization in the bandit setting: gradient descent without a gradient (488 citations)
- Efficient algorithms for online decision problems (479 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Artificial intelligence, Machine learning, Mathematical optimization, Theoretical computer science and Algorithm.
His work deals with themes such as Crowdsourcing and Natural language processing, which intersect with Artificial intelligence.
Many of his research projects under Mathematical optimization are closely connected to Lipschitz continuity, Constant and Polynomial with Lipschitz continuity, Constant and Polynomial, tying the diverse disciplines of science together.
The Algorithm study combines topics in areas such as Test data, Computational learning theory and VC dimension.
His Unsupervised learning study integrates concerns from other disciplines, such as Supervised learning and Cluster analysis.
His research integrates issues of Method of moments, Univariate and Estimator in his study of Applied mathematics.
He most often published in these fields:
- Artificial intelligence (34.46%)
- Machine learning (20.27%)
- Mathematical optimization (13.51%)
What were the highlights of his more recent work (between 2018-2021)?
- VC dimension (4.05%)
- Artificial intelligence (34.46%)
- Theoretical computer science (12.84%)
In recent papers he was focusing on the following fields of study:
Adam Tauman Kalai mainly investigates VC dimension, Artificial intelligence, Theoretical computer science, BIOS and Classifier.
His study looks at the intersection of VC dimension and topics like Adversarial system with Transduction, Binary classification, Covariate shift and Test.
His research ties Machine learning and Artificial intelligence together.
His biological study spans a wide range of topics, including Linear programming, Online algorithm, String searching algorithm and Pruning.
Adam Tauman Kalai combines subjects such as Crowdsourcing and Natural language processing with his study of Word.
His Natural language processing research is multidisciplinary, relying on both Embedding and Cluster analysis.
Between 2018 and 2021, his most popular works were:
- Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting (50 citations)
- What are the Biases in My Word Embedding (38 citations)
- The disparate equilibria of algorithmic decision making when individuals invest rationally (18 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
His primary scientific interests are in Theoretical computer science, BIOS, Artificial intelligence, Word embedding and Proxy.
His Theoretical computer science study incorporates themes from Efficient algorithm, Standard algorithms and String searching algorithm.
His BIOS research incorporates a variety of disciplines, including Classifier, Machine learning, Cognitive psychology, Gender bias and Supervised learning.
His research on Artificial intelligence frequently links to adjacent areas such as Natural language processing.
Adam Tauman Kalai frequently studies issues relating to Crowdsourcing and Word embedding.
Proxy and Semantic representation are frequently intertwined in his study.
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