Maxim Raginsky
- Non-convex learning via Stochastic Gradient Langevin Dynamics: a\n nonasymptotic analysis
2017/02/13 by Maxim Raginsky, Raginsky, Maxim, Alexander Rakhlin +3 · 27 citations
Computer Science · Engineering · Mathematics · Medicine · #Advanced Neuroimaging Techniques and Applications #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Optimization and Control (math.OC) #Probability (math.PR) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Theoretical guarantees for sampling and inference in generative models\n with latent diffusions
2019/03/04 by Belinda Tzen, Tzen, Belinda, Maxim Raginsky +1 · 10 citations
Computer Science · Physics and Astronomy · #Generative Adversarial Networks and Image Synthesis #Neural Networks and Applications #Model Reduction and Neural Networks
- Generalization Bounds: Perspectives from Information Theory and PAC-Bayes
2023/09/08 by Fredrik Hellström, Giuseppe Durisi, Hellström, Fredrik +5 · 2 voices · 11 citations
Computer Science · Physics and Astronomy · #Bayesian Modeling and Causal Inference #Face and Expression Recognition #Statistical Mechanics and Entropy #cs.AI #cs.IT #cs.LG #math.ST #stat.ML
- A fidelity measure for quantum channels
2001/07/23 by Maxim Raginsky · 5 citations
Physics and Astronomy · #quant-ph
- Quantum system identification
2003/06/02 by Maxim Raginsky, Raginsky, Maxim · 5 citations
Physics and Astronomy · #FOS: Physical sciences #Quantum Physics (quant-ph) #quant-ph
- Strong data processing inequalities and Φ-Sobolev inequalities for discrete channels
2014/11/13 by Maxim Raginsky, Raginsky, Maxim · 6 citations
Computer Science · Decision Sciences · #Adversarial Robustness in Machine Learning #Probabilistic and Robust Engineering Design
- Information-Theoretic Lower Bounds on Bayes Risk in Decentralized Estimation
2016/07/02 by Aolin Xu, Maxim Raginsky, Xu, Aolin +1 · 3 citations
Computer Science · Engineering · #Distributed Sensor Networks and Detection Algorithms #Wireless Communication Security Techniques #Target Tracking and Data Fusion in Sensor Networks
- Radon-Nikodym derivatives of quantum operations
2003/03/31 by Maxim Raginsky · 2 citations
Physics and Astronomy · Mathematics · #math-ph #math.MP #math.OA #quant-ph #msc:46L07 #msc:46L55 #msc:46L60 #msc:47L07
- Concentration of measure without independence: a unified approach via the martingale method
2016/02/01 by Aryeh Kontorovich, Kontorovich, Aryeh, Maxim Raginsky +1 · 2 citations
Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Markov Chains and Monte Carlo Methods #Probability (math.PR)
- Entropy production rates of bistochastic strictly contractive quantum channels on a matrix algebra
2002/07/31 by Maxim Raginsky · 1 citation
Computer Science · Mathematics · Physics and Astronomy · #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Mechanics and Applications #cond-mat.stat-mech #math-ph #math.MP #math.OA #quant-ph
- Information-based complexity, feedback and dynamics in convex programming
2010/10/12 by Maxim Raginsky, Alexander Rakhlin, Raginsky, Maxim +1 · 1 citation
Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Information Theory (cs.IT) #Machine Learning and Algorithms #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Systems and Control (eess.SY) #electronic engineering #information engineering
- Online Markov decision processes with Kullback-Leibler control cost
2014/01/14 by Peng Guan, Maxim Raginsky, Guan, Peng +3 · 1 citation
Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Optimization and Search Problems #Reinforcement Learning in Robotics #Systems and Control (eess.SY) #electronic engineering #information engineering
- Can Transformers Learn to Solve Problems Recursively?
2023/05/24 by Shizhuo Dylan Zhang, Curt Tigges, Zhang, Shizhuo Dylan +7 · 2 citations
Computer Science · #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Logic in Computer Science (cs.LO) #Machine Learning (cs.LG) #Programming Languages (cs.PL) #Software Engineering Research
- Learning finite-dimensional coding schemes with nonlinear reconstruction\n maps
2018/12/23 by Jae-Ho Lee, Lee, Jaeho, Maxim Raginsky +1 · 1 citation
Mathematics · Computer Science · #Statistical Methods and Inference #Markov Chains and Monte Carlo Methods #Topological and Geometric Data Analysis
- Minimum Excess Risk in Bayesian Learning
2020/12/29 by Aolin Xu, Xu, Aolin, Maxim Raginsky +1 · 1 citation
Computer Science · #Artificial Intelligence (cs.AI) #Bayesian Methods and Mixture Models #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Statistics Theory (math.ST)
- Talagrand Meets Talagrand: Upper and Lower Bounds on Expected Soft Maxima of Gaussian Processes with Finite Index Sets
2025/02/10 by Yifeng Chu, Maxim Raginsky, Chu, Yifeng +1 · 2 voices · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #Gaussian Processes and Bayesian Inference #Gene Regulatory Network Analysis #Mathematical Biology Tumor Growth #math.PR
- Separating Geometry from Probability in the Analysis of Generalization
2026/04/21 by Maxim Raginsky, Benjamin Recht · 3 voices · 1 citation
#cs.LG #math.OC #stat.ML