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Poczos, Barnabas

  1. Deep Sets
    2017/03/10 by Zaheer, Manzil, Kottur, Satwik, Ravanbakhsh, Siamak +3 · 127 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  2. Gradient Descent Provably Optimizes Over-parameterized Neural Networks
    2018/10/04 by Du, Simon S., Zhai, Xiyu, Poczos, Barnabas +1 · 35 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  3. Stochastic Variance Reduction for Nonconvex Optimization
    2016/03/19 by Sashank J. Reddi, Reddi, Sashank J., Ahmed Hefny +7 · 37 citations
    Computer Science · Engineering · Mathematics · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Markov Chains and Monte Carlo Methods
  4. High Dimensional Bayesian Optimisation and Bandits via Additive Models
    2015/03/05 by Kirthevasan Kandasamy, Kandasamy, Kirthevasan, Jeff Schneider +3 · 19 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
  5. Found in Translation: Learning Robust Joint Representations by Cyclic Translations Between Modalities
    2018/12/19 by Hai Pham, Paul Pu Liang, Pham, Hai +7 · 13 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
  6. 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
  7. Multi-fidelity Bayesian Optimisation with Continuous Approximations
    2017/03/18 by Kandasamy, Kirthevasan, Dasarathy, Gautam, Schneider, Jeff +1 · 8 citations
    #FOS: Computer and information sciences #Machine Learning (stat.ML)
  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. Equivariance Through Parameter-Sharing
    2017/02/27 by Siamak Ravanbakhsh, Jeff Schneider, Ravanbakhsh, Siamak +3 · 6 citations
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Machine Learning and Algorithms #Model Reduction and Neural Networks #Neural and Evolutionary Computing (cs.NE)
  10. Stochastic Frank-Wolfe Methods for Nonconvex Optimization
    2016/07/27 by Reddi, Sashank J., Sra, Suvrit, Poczos, Barnabas +1 · 5 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  11. Gradient Descent Can Take Exponential Time to Escape Saddle Points
    2017/05/29 by Du, Simon S., Jin, Chi, Lee, Jason D. +3 · 5 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  12. Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing
    2015/08/04 by Ramdas, Aaditya, Reddi, Sashank J., Poczos, Barnabas +2 · 4 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
  13. Nonparametric Estimation of Renyi Divergence and Friends
    2014/02/12 by Krishnamurthy, Akshay, Kandasamy, Kirthevasan, Poczos, Barnabas +1 · 2 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Statistics Theory (math.ST)
  14. Boolean Matrix Factorization and Noisy Completion via Message Passing
    2015/09/28 by Ravanbakhsh, Siamak, Poczos, Barnabas, Greiner, Russell · 2 citations
    #Artificial Intelligence (cs.AI) #Discrete Mathematics (cs.DM) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Statistics Theory (math.ST)
  15. Multi-fidelity Gaussian Process Bandit Optimisation
    2016/03/20 by Kandasamy, Kirthevasan, Dasarathy, Gautam, Oliva, Junier B. +2 · 2 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  16. Estimating Cosmological Parameters from the Dark Matter Distribution
    2017/11/06 by Ravanbakhsh, Siamak, Oliva, Junier, Fromenteau, Sebastien +4 · 2 citations
    #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  17. Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly
    2019/03/15 by Kirthevasan Kandasamy, Karun Raju Vysyaraju, Kandasamy, Kirthevasan +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
  18. The Role of Machine Learning in the Next Decade of Cosmology
    2019/02/26 by Michelle Ntampaka, Camille Avestruz, Ntampaka, Michelle +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)
  19. Politeness Transfer: A Tag and Generate Approach
    2020/04/29 by Madaan, Aman, Setlur, Amrith, Parekh, Tanmay +6 · 2 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences
  20. Deep Learning with Sets and Point Clouds
    2016/11/14 by Siamak Ravanbakhsh, Jeff Schneider, Ravanbakhsh, Siamak +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)
  21. Copula-based Kernel Dependency Measures
    2012/06/18 by Poczos, Barnabas, Ghahramani, Zoubin, Schneider, Jeff · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
  22. Fast Incremental Method for Nonconvex Optimization
    2016/03/19 by Reddi, Sashank J., Sra, Suvrit, Poczos, Barnabas +1 · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  23. Enabling Dark Energy Science with Deep Generative Models of Galaxy Images
    2016/09/19 by Ravanbakhsh, Siamak, Lanusse, Francois, Mandelbaum, Rachel +2 · 1 citation
    #Artificial Intelligence (cs.AI) #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Computer and information sciences #FOS: Physical sciences #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Machine Learning (stat.ML)
  24. Asynchronous Parallel Bayesian Optimisation via Thompson Sampling
    2017/05/25 by Kandasamy, Kirthevasan, Krishnamurthy, Akshay, Schneider, Jeff +1 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  25. Point Cloud GAN
    2018/10/13 by Li, Chun-Liang, Zaheer, Manzil, Zhang, Yang +2 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  26. Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction
    2020/09/17 by Toneva, Mariya, Stretcu, Otilia, Poczos, Barnabas +2 · 1 citation
    #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  27. Task-Based MoE for Multitask Multilingual Machine Translation
    2023/08/30 by Pham, Hai, Kim, Young Jin, Mukherjee, Subhabrata +3 · 1 citation
    #Computation and Language (cs.CL) #FOS: Computer and information sciences
  28. 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
  29. 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)