What is local optimality in nonconvex-nonconcave minimax optimization? networks, Exploiting tractable substructures in intractable networks, An internal forward model for sensorimotor integration, Are arm trajectories planned in kinematic or dynamic coordinates?
%%EOF Is there an analog of Nesterov acceleration for MCMC? By continuing to browse our site, you agree to the use of these cookies. EM algorithm based on finite Gaussian mixtures. 0000012988 00000 n A competitive modular connectionist architecture. Simultaneous relevant feature identification and classification A dynamical model of priming and repetition blindness. single-cell RNA sequencing, Communication-efficient distributed statistical inference, On kernel methods for covariates that are rankings, Covariances, robustness, and variational Bayes, CoCoA: A general framework for communication-efficient distributed optimization, Posteriors, conjugacy, and exponential families for completely random measures, Latent marked Poisson process with applications to object segmentation, Ray: A distributed framework for emerging AI applications, Asynchronous online testing of multiple hypotheses, Understanding the acceleration phenomenon via high-resolution differential equations, Evaluating sensitivity to the stick breaking prior in Bayesian nonparametrics, A deep generative model for semi-supervised classification with noisy labels, Sharp convergence rates for Langevin dynamics in the nonconvex setting, Learning without mixing: Towards a sharp analysis of linear system identification, Underdamped Langevin MCMC: A non-asymptotic analysis, Averaging stochastic gradient descent on Riemannian manifolds, Accelerated gradient descent escapes saddle points faster than gradient descent, Detection limits in the high-dimensional spiked rectangular model, Partial transfer learning with selective adversarial networks, SAFFRON: An adaptive algorithm for online control of the false discovery rate, Learning to explain: An information-theoretic perspective on model interpretation, Ray RLlib: A framework for distributed reinforcement learning, On the theory of variance reduction for stochastic gradient Monte Carlo, Flexible primitives for distributed deep learning in Ray, Minimizing nonconvex population risk from rough empirical risk, On nonlinear dimensionality reduction, linear smoothing and autoencoding, Model-based value estimation for efficient model-free reinforcement learning, Gradient descent can take exponential time to escape saddle points, Nonconvex finite-sum optimization via SCSG methods, Online control of the false discovery rate with decaying memory, Fast black-box variational inference through stochastic trust-region optimization, Kernel feature selection via conditional covariance minimization, Minimax optimal procedures for locally private estimation, Perturbed iterate analysis for asynchronous stochastic optimization, Finite size corrections and likelihood ratio fluctuations in the spiked Wigner model, Measuring cluster stability for Bayesian nonparametrics using the linear
Are reaching movements planned to be straight and invariant in Paris Saint-Germain Logo. In G. Tesauro, D. S. Touretzky and T. K. Leen, (Eds.). This site should not be used to make decisions about employment, tenant screening, or any purpose covered by the FCRA.The records were matched using first and last name only. Zhang, M. Wainwright, and M. I. Jordan. exponential families, Learning graphical models with Mercer kernels, A minimal intervention principle for coordinated movement, Finding clusters in independent component analysis, A hierarchical Bayesian Markovian model for motifs in biopolymer sequences, Integrated analysis of transcript profiling and protein sequence data, Distance metric learning, with application to clustering with side-information, Sampling user executions for bug isolation, Optimal feedback control as a theory of motor coordination, A robust minimax approach to classification, Sensorimotor adaptation of speech I: Compensation and adaptation, Graphical models: Probabilistic inference, Loopy belief propagation and Gibbs measures, Random sampling of a continuous-time stochastic dynamical system, On spectral clustering: Analysis and an algorithm, On discriminative vs. generative classifiers: A comparison of logistic
Jordan has 11 jobs listed on their profile. In other faculty news, Kenneth Wachter is investigating the interface between socio-genomics and family demography and serving on the Editorial Board of Proceedings of the National Academy of Science.
production of the vowel /u/: A pilot motor equivalence study. 0000003800 00000 n An introduction to linear algebra in parallel, distributed processing. distributions, Smoothness maximization along a predefined path accurately Jordan Brand. L. Xu and M. I. Jordan. trend filtering and l1-convex clustering, Acceleration via symplectic discretization of high-resolution differential equations, Transferable normalization: Towards improving transferability of deep neural networks, Quantitative central limit theorems for discrete stochastic processes, Challenges with EM in application to weakly identifiable mixture models, Minmax optimization: Stable limit points of gradient descent ascent are locally optimal, First-order methods almost always avoid strict saddle-points, A sequential algorithm for false discovery rate control on directed acyclic graphs, On finding local Nash equilibria (and only local Nash equilibria) in zero-sum games, Harmonization and annotation of single-cell transcriptomics data with deep generative Constraints on underspecified target trajectories. P. Mazzoni, R. Andersen, and M. I. Jordan. D. Cohn, Z. Ghahramani, and M. I. Jordan. Gender Identification Differences in U.S. performance requirements, Nonparametric Bayesian co-clustering ensembles, Dimensionality reduction for spectral clustering, Message from the President: Visualizing Bayesians, Supervised hierarchical Pitman-Yor process for natural scene segmentation, A unified probabilistic model for global and local unsupervised feature selection, Message from the President: The era of Big Data, Managing data transfers in computer clusters with Orchestra, Visually relating gene expression and in vivo DNA binding data. It is held as a preconference sess... more. 138 0 obj<>stream
M. Hirayama, E. Vatikiotis-Bateson, M. Kawato, and M. I. Jordan. For a given clique C,let ψ C(x C) denote a general potential function—a function that assigns a positive real number to each conﬁguration x
penalized convex risk minimization, A direct formulation for sparse PCA using semidefinite programming, A randomization test for controlling population stratification in
Will Dow and I have both accepted joint-appointments in Demography. Hierarchies of adaptive experts.
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