vix.ing · top · new · best · stats · spec

Jordan, Michael

  1. High-Dimensional Continuous Control Using Generalized Advantage\n Estimation
    2015/06/08 by John Schulman, Schulman, John, Philipp Moritz +7 · 287 citations
    Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Electrical engineering #Machine Learning (cs.LG) #Prosthetics and Rehabilitation Robotics #Real-time simulation and control systems #Reinforcement Learning in Robotics #Robotic Locomotion and Control #Robotics (cs.RO) #Systems and Control (eess.SY) #electronic engineering #information engineering
  2. Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference
    2024/03/07 by Chiang, Wei-Lin, Zheng, Lianmin, Sheng, Ying +8 · 250 citations
    #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences
  3. Variational Bayesian Inference with Stochastic Search
    2012/06/27 by John Paisley, David M. Blei, Paisley, John +3 · 24 citations
    Computer Science · #Bayesian Methods and Mixture Models #Gaussian Processes and Bayesian Inference #Machine Learning and Algorithms
  4. Minimax Optimal Procedures for Locally Private Estimation
    2016/04/08 by Duchi, John, Wainwright, Martin, Jordan, Michael · 10 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Methodology (stat.ME) #Statistics Theory (math.ST)
  5. An Analysis of the Convergence of Graph Laplacians
    2011/01/28 by Daniel Ting, Ting, Daniel, Ling Huang +3 · 5 citations
    Computer Science · Mathematics · #Advanced Graph Theory Research #FOS: Computer and information sciences #Graph theory and applications #Machine Learning (stat.ML) #Topological and Geometric Data Analysis
  6. Doubly Robust Self-Training
    2023/06/01 by Banghua Zhu, Zhu, Banghua, Mingyu Ding +11 · 7 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #Video Surveillance and Tracking Methods #Advanced Neural Network Applications
  7. Rank Diminishing in Deep Neural Networks
    2022/06/13 by Ruili Feng, Feng, Ruili, Kecheng Zheng +9 · 5 citations
    Computer Science · Engineering · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Medical Image Segmentation Techniques #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  8. Classifier Calibration with ROC-Regularized Isotonic Regression
    2023/11/21 by Berta, Eugene, Bach, Francis, Jordan, Michael · 6 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  9. Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics
    2024/05/07 by Hanlin Zhu, Zhu, Hanlin, Baihe Huang +11 · 7 citations
    Computer Science · #Topic Modeling #Multimodal Machine Learning Applications #Text Readability and Simplification
  10. Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences
    2016/09/04 by Jin, Chi, Zhang, Yuchen, Balakrishnan, Sivaraman +2 · 2 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  11. SAFFRON: an adaptive algorithm for online control of the false discovery rate
    2018/02/25 by Aaditya Ramdas, Ramdas, Aaditya, Tijana Zrnic +5 · 2 citations
    Computer Science · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning and Algorithms #Methodology (stat.ME) #Statistical Methods and Bayesian Inference #Statistical Methods in Clinical Trials #Statistics Theory (math.ST)
  12. Linear Response Methods for Accurate Covariance Estimates from Mean\n Field Variational Bayes
    2015/06/12 by Ryan Giordano, Giordano, Ryan, Tamara Broderick +3 · 3 citations
    Computer Science · Decision Sciences · Mathematics · #Advanced Multi-Objective Optimization Algorithms #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Probabilistic and Robust Engineering Design #Statistical Methods and Bayesian Inference
  13. DAVED: Data Acquisition via Experimental Design for Data Markets
    2024/03/20 by Lu, Charles, Huang, Baihe, Karimireddy, Sai Praneeth +3 · 3 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  14. On Learning Necessary and Sufficient Causal Graphs
    2023/01/29 by Hengrui Cai, Cai, Hengrui, Zhaoran Wang +5 · 2 citations
    Biochemistry, Genetics and Molecular Biology · Computer Science · #Advanced Graph Neural Networks #Applications (stat.AP) #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #Bioinformatics and Genomic Networks #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME)
  15. A deep generative model for gene expression profiles from single-cell RNA sequencing
    2017/09/07 by Romain Lopez, Jeffrey Regier, Lopez, Romain +7 · 1 citation
    Biochemistry, Genetics and Molecular Biology · Computer Science · #Cancer-related molecular mechanisms research #Evolutionary Algorithms and Applications #FOS: Biological sciences #FOS: Computer and information sciences #Genomics (q-bio.GN) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Single-cell and spatial transcriptomics
  16. Provably Personalized and Robust Federated Learning
    2023/06/14 by Mariel Werner, Werner, Mariel, Lie He +7 · 1 citation
    Computer Science · Decision Sciences · Mathematics · #Data Quality and Management #Distributed #FOS: Computer and information sciences #Machine Learning (cs.LG) #Parallel #Privacy-Preserving Technologies in Data #Statistical Methods and Inference #and Cluster Computing (cs.DC)
  17. The Big Data Bootstrap
    2012/06/27 by Ariel Kleiner, Kleiner, Ariel, Ameet Talwalkar +5 · 2 citations
    Computer Science · Mathematics · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Statistical Methods and Inference
  18. Learning Variational Inequalities from Data: Fast Generalization Rates under Strong Monotonicity
    2024/10/28 by Eric Y. Stutheit-Zhao, Zhao, Eric, Tatjana Chavdarova +3 · 1 citation
    Computer Science · Mathematics · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Mathematics #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Statistical Methods and Inference