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Machine Learning and Algorithms

Machine Learning and Algorithms

208 faculty research Machine Learning and Algorithms on GradNova.

N
Algorithmic and Complexity Theory
Circuit Complexity
Coding Theory
Fourier Analysis of Boolean Functions
+7
A
Advanced Bandit Algorithms Research
Machine Learning and Algorithms
Optimization and Search Problems
Sparse and Compressive Sensing Techniques
+1
J
Algorithms and Data Compression
Complexity and Algorithms in Graphs
Computability, Logic, AI Algorithms
Machine Learning and Algorithms
+1
N
Advanced Graph Theory Research
Complexity and Algorithms in Graphs
Machine Learning and Algorithms
Markov Chains and Monte Carlo Methods
+1
A
Bayesian Modeling and Causal Inference
Formal Methods in Verification
Logic, Programming, and Type Systems
Machine Learning and Algorithms
+1
O
Machine Learning and Algorithms
Markov Chains and Monte Carlo Methods
Random Matrices and Applications
Statistical Methods and Inference
+1
D
Discrete Mathematics
Machine Learning
Neural Networks
Probability Theory
+6
C
Cognitive Modeling
Data Mining and Its Applications
Machine Learning
Machine Learning and Data Classification
+4
B
AI-Based Problem Solving and Planning
Bayesian Modeling and Causal Inference
Logic, Reasoning, and Knowledge
Machine Learning and Algorithms
+1
R
Advanced Bandit Algorithms Research
Advanced Multi-Objective Optimization Algorithms
Gaussian Processes and Bayesian Inference
Machine Learning and Algorithms
+1
T
Advanced Bandit Algorithms Research
Adversarial Robustness in Machine Learning
Machine Learning and Algorithms
Reinforcement Learning in Robotics
+1
S
Complexity and Algorithms in Graphs
Cryptography and Data Security
Machine Learning and Algorithms
Sparse and Compressive Sensing Techniques
+1
D
Complexity and Algorithms in Graphs
Computability, Logic, AI Algorithms
Cryptography and Data Security
Machine Learning and Algorithms
+1
K
Advanced Bandit Algorithms Research
Auction Theory and Applications
Gaussian Processes and Bayesian Inference
Machine Learning and Algorithms
+1
J
Machine Learning and Algorithms
Reinforcement Learning in Robotics
Robot Manipulation and Learning
Traffic Control and Management
+1
J
Advanced Optimization Algorithms Research
Machine Learning and Algorithms
Optimization and Variational Analysis
Sparse and Compressive Sensing Techniques
+1
I
Algorithms and Data Compression
Complexity and Algorithms in Graphs
Machine Learning and Algorithms
Machine Learning and Data Classification
+1
Y
Yudong Chen

Sheldon B. and Marianne S. Lubar Professor

Computer Science

University of Wisconsin–Madison

Complex Network Analysis Techniques
Machine Learning and Algorithms
Sparse and Compressive Sensing Techniques
Statistical Methods and Inference
+1
P
Applications of Machine Learning in Natural Language Processing (conversational Agents, Grammar Error Correction, Automated Text Editing) and Material Design (bayesian Optimization of Catalysts, Oxygen Carriers and Other Materials to Facilitate Desirable Chemical Reactions for Co2 Conversion and Co2 Capture)
Machine Learning, Including Reinforcement Learning, Federated Learning, Continual Learning, Self-Supervised Learning, Meta Learning, Few Shot Learning, Causal Learning, Uncertainty Quantification and Calibration
Reinforcement Learning in Robotics
Topic Modeling
+3
G
Differential Privacy, Robustness
Machine Learning and Statistics
Theoretical Computer Science
Privacy-Preserving Technologies in Data
+4
M
High-Recall Information Retrieval, in Which the Goal Is to Find Substantially All Information Relevant to an Information Need With the Least Possible Effort, Where the Stakes of Missing Relevant Information Are High
Key Application Areas Include Electronic Discovery in Law, Curation of Government Archives, and Systematic Review in Evidence-Based Medicine
Responsible AI and Data Science, Which Includes, but Is Not Limited To, Legal, Ethical, and Policy Considerations
Topic Modeling
+4
E
Randomized
Complexity Theory
Randomized and Sublinear-Time Algorithms
Complexity and Algorithms in Graphs
+4
S
Computational Complexity
Quantum Computing
Complexity and Algorithms in Graphs
Machine Learning and Algorithms
+3
S
Alternatives to Worst-Case Complexity
Domain Adaptation and Transfer Learning
Fairness, Reliability and Interpretability of Machine Learning-Based Tools
Logic and Its Applications to Computer Science Theory
+7
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