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Barnabás Póczos

  1. MMD GAN: Towards Deeper Understanding of Moment Matching Network
    2017/05/24 by Chunliang Li, Wei-Cheng Chang, Li, Chun-Liang +7 · 27 citations
    Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Human Pose and Action Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Music and Audio Processing
  2. Stochastic Variance Reduction for Nonconvex Optimization
    2016/03/19 by Sashank J. Reddi, Reddi, Sashank J., Ahmed Hefny +7 · 31 citations
    Computer Science · Engineering · Mathematics · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Markov Chains and Monte Carlo Methods
  3. High Dimensional Bayesian Optimisation and Bandits via Additive Models
    2015/03/05 by Kirthevasan Kandasamy, Kandasamy, Kirthevasan, Jeff Schneider +3 · 17 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
  4. Characterizing and Avoiding Negative Transfer
    2018/11/24 by Zirui Wang, Zihang Dai, Wang, Zirui +5 · 15 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Multimodal Machine Learning Applications
  5. A Flexible Framework for Multi-Objective Bayesian Optimization using\n Random Scalarizations
    2018/05/30 by Biswajit Paria, Kirthevasan Kandasamy, Paria, Biswajit +3 · 14 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  6. Found in Translation: Learning Robust Joint Representations by Cyclic Translations Between Modalities
    2018/12/19 by Hai Pham, Paul Pu Liang, Pham, Hai +7 · 12 citations
    Computer Science · #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Multimodal Machine Learning Applications #Sentiment Analysis and Opinion Mining #Topic Modeling
  7. ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations
    2019/08/05 by Ksenia Korovina, Korovina, Ksenia, Sailun Xu +11 · 11 citations
    Computer Science · Materials Science · Engineering · #Computational Drug Discovery Methods #Machine Learning in Materials Science #Process Optimization and Integration
  8. Nonparametric Divergence Estimation with Applications to Machine\n Learning on Distributions
    2012/02/14 by Barnabás Póczos, Liang Xiong, Poczos, Barnabas +3 · 8 citations
    Computer Science · #Bayesian Methods and Mixture Models #Anomaly Detection Techniques and Applications #Gaussian Processes and Bayesian Inference
  9. Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels
    2019/05/30 by Simon S. Du, Du, Simon S., Kangcheng Hou +9 · 7 citations
    Computer Science · #Advanced Graph Neural Networks #Advanced Neural Network Applications #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Topic Modeling
  10. Estimation of R 'enyi Entropy and Mutual Information Based on\n Generalized Nearest-Neighbor Graphs
    2010/03/09 by Dávid Pál, Pál, Dávid, Barnabás Póczos +3 · 4 citations
    Computer Science · Mathematics · #Artificial Intelligence (cs.AI) #Bayesian Methods and Mixture Models #Blind Source Separation Techniques #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (stat.ML) #Statistical Methods and Inference
  11. Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators
    2016/06/05 by Shashank Kumar Singh, Singh, Shashank, Barnabás Póczos +2 · 3 citations
    Computer Science · Mathematics · #Advanced Statistical Methods and Models #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Information Theory (cs.IT) #Machine Learning (stat.ML) #Statistical Methods and Inference #Statistics Theory (math.ST)
  12. Analysis of k-Nearest Neighbor Distances with Application to Entropy Estimation
    2016/03/28 by Shashank Singh, Barnabás Póczos, Singh, Shashank +1 · 4 citations
    Computer Science · Mathematics · #Advanced Statistical Methods and Models #FOS: Computer and information sciences #FOS: Mathematics #Face and Expression Recognition #Information Theory (cs.IT) #Machine Learning (stat.ML) #Statistical Methods and Inference #Statistics Theory (math.ST)
  13. Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses
    2019/02/09 by Ananya Uppal, Uppal, Ananya, Shashank Singh +3 · 2 citations
    Computer Science · Mathematics · #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Statistical Methods and Inference #Statistics Theory (math.ST)
  14. Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly
    2019/03/15 by Kirthevasan Kandasamy, Kandasamy, Kirthevasan, Karun Raju Vysyaraju +13 · 2 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Advanced Multi-Objective Optimization Algorithms #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
  15. The Role of Machine Learning in the Next Decade of Cosmology
    2019/02/26 by Michelle Ntampaka, Ntampaka, Michelle, Camille Avestruz +57 · 2 citations
    Physics and Astronomy · #Astronomy and Astrophysical Research #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Physical sciences #Galaxies: Formation, Evolution, Phenomena #Gamma-ray bursts and supernovae #Instrumentation and Methods for Astrophysics (astro-ph.IM)
  16. Implicit Kernel Learning
    2019/02/26 by Chunliang Li, Li, Chun-Liang, Wei-Cheng Chang +7 · 3 citations
    Computer Science · Physics and Astronomy · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Music and Audio Processing
  17. Deep Learning with Sets and Point Clouds
    2016/11/14 by Siamak Ravanbakhsh, Ravanbakhsh, Siamak, Jeff Schneider +3 · 3 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural and Evolutionary Computing (cs.NE)
  18. Generalized Exponential Concentration Inequality for R 'enyi Divergence\n Estimation
    2016/03/28 by Shashank Kumar Singh, Singh, Shashank, Barnabás Póczos +1 · 1 citation
    Computer Science · Engineering · Mathematics · #Distributed Sensor Networks and Detection Algorithms #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference #Statistics Theory (math.ST)
  19. Nonparanormal Information Estimation
    2017/02/24 by Shashank Singh, Singh, Shashank, Barnabás Póczos +1 · 1 citation
    Computer Science · Mathematics · #Advanced Statistical Methods and Models #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Machine Learning (stat.ML) #Statistical Methods and Inference #Statistics Theory (math.ST)
  20. Kernels on Sample Sets via Nonparametric Divergence Estimates
    2012/02/01 by Danica J. Sutherland, Liang Xiong, Sutherland, Danica J. +5 · 1 citation
    Computer Science · #Advanced Image and Video Retrieval Techniques #FOS: Computer and information sciences #Face and Expression Recognition #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  21. Minimax Distribution Estimation in Wasserstein Distance
    2018/02/24 by Shashank Singh, Singh, Shashank, Barnabás Póczos +1 · 1 citation
    Mathematics · Decision Sciences · #Point processes and geometric inequalities #Geometric Analysis and Curvature Flows #Risk and Portfolio Optimization
  22. Controllable Text Generation in the Instruction-Tuning Era
    2024/05/02 by Dhananjay Ashok, Ashok, Dhananjay, Barnabás Póczos +1 · 1 citation
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Intelligent Tutoring Systems and Adaptive Learning #Natural Language Processing Techniques
  23. Recovering Time-Varying Networks From Single-Cell Data
    2024/10/01 by Euxhen Hasanaj, Barnabás Póczos, Hasanaj, Euxhen +3 · 1 citation
    Biochemistry, Genetics and Molecular Biology · Neuroscience · #Bioinformatics and Genomic Networks #FOS: Biological sciences #FOS: Computer and information sciences #Functional Brain Connectivity Studies #Machine Learning (cs.LG) #Quantitative Methods (q-bio.QM)
  24. Two-stage Sampled Learning Theory on Distributions
    2014/02/07 by Zoltán Szabó, Szabo, Zoltan, Arthur Gretton +5 · 1 citation
    Computer Science · #46E22 #47B32 #62G08 #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Mathematics #Functional Analysis (math.FA) #G.3 #I.2.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Statistics Theory (math.ST)