Roosta, Fred

1. The reproducing Stein kernel approach for post-hoc corrected sampling
   2020/01/25 by Hodgkinson, Liam, Salomone, Robert, Roosta, Fred · 3 citations
   #60B10 (Secondary) #65C05 (Primary) 60J22 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Statistics Theory (math.ST)
2. Average-reward model-free reinforcement learning: a systematic review and literature mapping
   2020/10/18 by Vektor Dewanto, George Dunn, Dewanto, Vektor +7 · 3 citations
   Computer Science · Engineering · Business, Management and Accounting · #Reinforcement Learning in Robotics #Traffic control and management #Supply Chain and Inventory Management
3. Implicit Langevin Algorithms for Sampling From Log-concave Densities
   2019/03/29 by Liam Hodgkinson, Robert Salomone, Hodgkinson, Liam +3 · 2 citations
   Economics, Econometrics and Finance · Mathematics · #Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Statistical Methods and Inference #Stochastic processes and financial applications
4. Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution
   2024/05/16 by Eslam Zaher, Zaher, Eslam, Maciej Trzaskowski +5 · 4 citations
   Computer Science · Engineering · #Advanced Numerical Analysis Techniques #Differential Geometry (math.DG) #FOS: Computer and information sciences #FOS: Mathematics #Human-Computer Interaction (cs.HC) #Machine Learning (cs.LG) #Medical Image Segmentation Techniques #Medical Imaging and Analysis
5. Inexact Newton-CG Algorithms With Complexity Guarantees
   2021/09/28 by Yao, Zhewei, Xu, Peng, Roosta, Fred +2 · 2 citations
   #FOS: Mathematics #Optimization and Control (math.OC)
6. Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes
   2022/10/14 by Hodgkinson, Liam, van der Heide, Chris, Roosta, Fred +1 · 2 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
7. DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization
   2019/01/16 by Rixon Crane, Fred Roosta, Crane, Rixon +1 · 1 citation
   Engineering · Computer Science · Mathematics · #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #Advanced Optimization Algorithms Research
8. Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings
   2019/09/29 by Levin, Keith, Roosta, Fred, Tang, Minh +2 · 1 citation
   #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Statistics Theory (math.ST)
9. LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of Big Time Series Data
   2019/11/27 by Ali Eshragh, Fred Roosta, Eshragh, Ali +5 · 1 citation
   Computer Science · Mathematics · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Methodology (stat.ME) #Neural Networks and Applications #Statistical Methods and Inference
10. Richer priors for infinitely wide multi-layer perceptrons
    2019/11/29 by Russell Tsuchida, Tsuchida, Russell, Fred Roosta +3 · 1 citation
    Computer Science · #Blind Source Separation Techniques #FOS: Computer and information sciences #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
11. MINRES: From Negative Curvature Detection to Monotonicity Properties
    2022/06/12 by Liu, Yang, Roosta, Fred · 1 citation
    #FOS: Mathematics #Optimization and Control (math.OC)
12. A Newton-MR algorithm with complexity guarantees for nonconvex smooth unconstrained optimization
    2022/08/15 by Yang Liu, Liu, Yang, Fred Roosta +1 · 1 citation
    Computer Science · Engineering · Mathematics · #Advanced Optimization Algorithms Research #FOS: Mathematics #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
13. The Interpolating Information Criterion for Overparameterized Models
    2023/07/15 by Liam Hodgkinson, Chris van der Heide, Hodgkinson, Liam +7 · 2 citations
    Mathematics · Computer Science · #Statistical Methods and Inference #Bayesian Methods and Mixture Models #Statistical Methods and Bayesian Inference
14. Stochastic Normalizing Flows
    2020/02/21 by Liam Hodgkinson, Hodgkinson, Liam, Chris van der Heide +5 · 2 citations
    Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis
15. First-ish Order Methods: Hessian-aware Scalings of Gradient Descent
    2025/02/06 by Oscar Smee, Fred Roosta, Smee, Oscar +3 · 1 citation
    Computer Science · Physics and Astronomy · #49 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques