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Stochastic Gradient Optimization Techniques

Stochastic Gradient Optimization Techniques

131 faculty research Stochastic Gradient Optimization Techniques on GradNova.

R
Generative Adversarial Networks and Image Synthesis
Machine Learning in Materials Science
Model Reduction and Neural Networks
Stochastic Gradient Optimization Techniques
L
Industrial and Systems Engineering
Machine Learning
Stochastic Gradient Optimization Techniques
Advanced Optimization Algorithms Research
+3
N
Naichen Shi

Assistant Professor of Industrial Engineering and Management Sciences and Mechanical Engineering

Department of Mechanical Engineering

Northwestern University

Advanced Manufacturing
AI and Design
Computational Engineering
Stochastic Gradient Optimization Techniques
+4
S
Machine Learning
Multi-Agent Systems
Optimization and Control
Reinforcement Learning
+5
L
Control Theory
Linear Systems
Machine Learning
Optimization Algorithms
+5
N
Domain Adaptation and Few-Shot Learning
Model Reduction and Neural Networks
Smart Grid Energy Management
Sparse and Compressive Sensing Techniques
+1
Y
Yuejie Chi

Secondary Faculty, Professor

Computer Science

Yale University

Blind Source Separation Techniques
Microwave Imaging and Scattering Analysis
Reinforcement Learning in Robotics
Sparse and Compressive Sensing Techniques
+1
J
Parallel Computing and Optimization Techniques
Quantum Computing Algorithms and Architecture
Quantum Information and Cryptography
Quantum Mechanics and Applications
+1
S
Advanced MIMO Systems Optimization
IoT and Edge/fog Computing
Privacy-Preserving Technologies in Data
Stochastic Gradient Optimization Techniques
+1
R
Signal Processing and Communication Systems: Efficient Utilization of Multiple Antennas for High-Rate Communications in Wireless Networks, Statistical Detection Methods for Underwater Acoustic Communications, and Other Fields Related to Communication Systems and Statistical Signal Processing.
Advanced Wireless Communication Techniques
Caching and Content Delivery
Stochastic Gradient Optimization Techniques
+2
S
Algorithmic Problems From Statistics and Machine Learning
Approximation Algorithms
Design of Fast Algorithms, Particularly for Graph Problems and Optimization
Numerical Linear Algebra
+7
M
Cloud Computing
Compilers
Computer Architecture
Graph Theory
+13
R
Bayesian Learning
Machine Learning
Neural Networks
Neural Networks and Applications
+4
M
Graphical Models
Machine Learning
Machine Learning Theory
Optimization Algorithms
+6
J
Deep Learning
Deep Reinforcement Learning
Machine Learning
Neural Networks
+6
M
Meisam Razaviyayn

Andrew and Erna Viterbi Early Career Chair and Associate Professor Industrial and Systems Engineering, Computer Science, and Electrical and Computer Engineering

Computer Science

University of Southern California

Advanced MIMO Systems Optimization
Cooperative Communication and Network Coding
Privacy-Preserving Technologies in Data
Sparse and Compressive Sensing Techniques
+1
S
Sai Praneeth Karimireddy

Assistant Professor of Computer Science and Electrical and Computer Engineering

Computer Science

University of Southern California

Adversarial Robustness in Machine Learning
Cryptography and Data Security
Privacy-Preserving Technologies in Data
Sparse and Compressive Sensing Techniques
+1
W
Weijie Su

Professor Statistics and Data Science Primary Computer and Information Science

Computer Science

University of Pennsylvania

Natural Language Processing Techniques
Privacy-Preserving Technologies in Data
Statistical Methods and Inference
Stochastic Gradient Optimization Techniques
+1
Z
Adversarial Robustness in Machine Learning
Cryptography and Data Security
Privacy-Preserving Technologies in Data
Stochastic Gradient Optimization Techniques
+1
M
Advanced MIMO Systems Optimization
Caching and Content Delivery
Cooperative Communication and Network Coding
Privacy-Preserving Technologies in Data
+1
M
Advanced MIMO Systems Optimization
Advanced Optimization Algorithms Research
Cooperative Communication and Network Coding
Sparse and Compressive Sensing Techniques
+1
Y
Yousef Saad

Professor, CSE Distinguished Professor, William Norris Land Grant Chair in Large-Scale Computing

Computer Science

University of Minnesota

Advanced Optimization Algorithms Research
Optimization and Variational Analysis
Stochastic Gradient Optimization Techniques
L
Lei Ying

Professor, EECS – Electrical and Computer Engineering

Department of Electrical and Computer Engineering

University of Michigan

The Interplay of Complex Stochastic Systems and Big-Data, Including Large-Scale Communication, Computing Systems for Reinforcement Learning, Big-Data Processing, Private Data Marketplaces, and Large-Scale Graph Mining
Advanced Bandit Algorithms Research
Advanced Queuing Theory Analysis
Stochastic Gradient Optimization Techniques
+2
Q
Qing Qu

Assistant Professor, EECS – Electrical and Computer Engineering

Department of Electrical and Computer Engineering

University of Michigan

Computational Imaging
High Dimensional Data Analysis
Machine Learning
Numerical Optimization
+6
2

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