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SMLG

    Spring 2025

  • 25 Apr 2025 Fair Group Shapley: Partition-Invariant and Computationally Efficient Group Data Valuation Ziqi Liu
  • 18 Apr 2025 Co-Training and its relationship to Missing Data Rebecca Farina
  • 11 Apr 2025 Inference for Online Algorithms without Variance Estimation Selina Carter
  • 04 Apr 2025 Graph Matching via the Projected Power Method and Mirror Descent Ernesto Araya
  • 28 Mar 2025 Causal Geodesy: Counterfactual Estimation Along the Path Between Correlation and Causation Kyle Schindl
  • 21 Mar 2025 Nonasymptotic and distribution-uniform Komlós-Major-Tusnády approximation Ian Waudby-Smith
  • 14 Mar 2025 Kandinsky Conformal Prediction Steven Wu
  • 28 Feb 2025 Martingale CLTs and Adaptive Linear Regression James Leiner
  • 21 Feb 2025 Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems Tomas Gonzalez
  • 14 Feb 2025 Off-Policy Evaluations of Linear Functionals: From Nonadaptive Semiparametric Efficiency to Adaptive Nonasymptotic Optimality Ojash Neopane
  • 07 Feb 2025 Discrete Argmin Inference Using Cross-Validated Exponential Mechanism Jing Lei
  • 31 Jan 2025 CLTs and Bagging Arun Kumar Kuchibhotla
  • Fall 2024

  • 03 Dec 2024 Statistical Properties of the rectified flow Gonzalo Mena
  • 26 Nov 2024 Empirical Bernstein inequalities for scalars and matrices Hongjian Wang
  • 19 Nov 2024 Dimension-agnostic inference for M-estimation Kenta Takatsu
  • 12 Nov 2024 Sequential Kernelized Stein Discrepancy Diego Martinez-Taboada
  • 29 Oct 2024 Markov Chain Variance Estimation: A Stochastic Approximation Approach Shubhada Agrawal
  • 22 Oct 2024 Conditional Independence Testing for High-dimensional Nonstationary Nonlinear Time Series Michael Wieck-Sosa
  • 11 Oct 2024 Bet and Belief Kai Zhang (UNC)
  • 01 Oct 2024 Sample complexity of causal effect estimation with discrete covariates Chandler Squires
  • 24 Sep 2024 Online Bootstrap Confidence Intervals for the Stochastic Gradient Descent Estimator Selina Carter
  • 17 Sep 2024 Demystifying Inference after Adaptive Experiments James Leiner
  • 10 Sep 2024 An introduction to the approximate message passing algorithm Yandi Shen
  • 05 Sep 2024 Some Recent Works in Generative Data Science Guang Chen (UCLA)
  • Spring 2024

  • 26 Apr 2024 Some recent results on the mixture NPMLE Tudor Manole
  • 19 Apr 2024 Geometry and analytic properties of the sliced Wasserstein space Sangmin Park
  • 12 Apr 2024 Optimal Conditional Inference in Adaptive Experiments James Leiner
  • 05 Apr 2024 Multivariate Symmetry: Distribution-Free Testing via Optimal Transport Gonzalo Mena
  • 29 Mar 2024 Model Selection Aggregation Siva Balakrishnan
  • 22 Mar 2024 Distribution-uniform strong laws of large numbers Ian Waudby-Smith
  • 15 Mar 2024 Active statistical inference Ben Chugg
  • 01 Mar 2024 When are Offline Multi-Agent Games Solvable? Simon Du
  • 23 Feb 2024 Distributions of approximately polynomial functions of high-dimensional data Kevin Han Huang
  • 16 Feb 2024 Performative Prediction: A New Approach to Social Science? Jamie Michelson
  • 09 Feb 2024 A 'robust' framework for statistical inference Arun Kuchibhotla
  • 02 Feb 2024 Statistical inference for model parameters in stochastic gradient descent Selina Carter
  • 26 Jan 2024 Domain Generalization with Adversarially Robust Learning: Identification, Estimation, and Uncertainty Quantification Zijian Guo (faculty visitor from Rutgers)
  • 19 Jan 2024 Merging Uncertainty Sets Via Majority Vote Aaditya Ramdas
  • Fall 2023

  • 30 Nov 2023 Minimax optimal testing by classification Lucas Kania
  • 16 Nov 2023 Inference for Projection Parameters in Linear Regression: beyond d=o(n^{1/2}) Woonyoung Chang
  • 09 Nov 2023 Spectral Regularized Kernel Two-Sample Tests Bharath Sriperumbudur (Faculty visitor from Penn State Statistics)
  • 02 Nov 2023 Beyond Neyman Pearson with e-values Neil Xu
  • 26 Oct 2023 Isotonic Distributional Regression Richard Zhu
  • 12 Oct 2023 Post-selection Inference for Conformal Prediction: Trading off Coverage for Precision Siddhaarth Sarkar
  • 05 Oct 2023 Representer Point Selection for Explaining Deep Neural Networks Alex Shen
  • 28 Sep 2023 Some topics on Gaussian and subGaussian SPRTs Hongjian Wang
  • 14 Sep 2023 Principal-agent hypothesis testing Ian Waudby-Smith
  • 07 Sep 2023 Empirical risk minimization and complexity of dynamical models James Carzon
  • Summer 2023

  • 12 Jul 2023 Empirical Optimal Transport: Convergence Rates and Lower Complexity Adaptation Shayan Hundrieser (Göttingen)
  • Spring 2023

  • 01 May 2023 Likelihood-free hypothesis testing James Carzon
  • 26 Apr 2023 An optimization-based approach to uncertainty quantification Kayla Scharfstein
  • 17 Apr 2023 Sequential change detection via backward confidence sequences Shubhanshu Shekar
  • 10 Apr 2023 A New Approach to Tests and Confidence Bands for Distribution Functions Siddhaarth Sarkar
  • 05 Apr 2023 High-dimensional Berry-Esseen Bound for m-Dependent Random Samples Heejong Bong
  • 29 Mar 2023 Multi-group agnostic learning via sleeping experts and adaptive hedging Chirag Gupta
  • 20 Mar 2023 Sequential Kernelized Independence Testing Sasha Podkopaev
  • 13 Mar 2023 Permutation tests for conditional independence Yuchen Chen
  • 27 Feb 2023 A short tutorial on negative dependence, with applications to multiple testing Aaditya Ramdas
  • 20 Feb 2023 Locally Simultaneous Inference Tijana Zrnic (Berkeley)
  • 13 Feb 2023 Median-of-Means Beomjo Park
  • 06 Feb 2023 Higher-order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes Diego Martinez-Taboada
  • 30 Jan 2023 Continuous Prediction with Experts’ Advice Ben Chugg
  • Fall 2022

  • 15 Nov 2022 Efficient Incentive-Compatible Forecasting Competitions YJ Choe
  • 08 Nov 2022 Multivariate Nonparametric Regression by the Method of Sieves Tianyu Zhang
  • 01 Nov 2022 Assumption-lean inference for generalised linear model parameters (Vansteelandt and Dukes) James Leiner
  • 25 Oct 2022 On nonparametric tests of positivity/monotonicity/convexity Kenta Takatsu
  • 11 Oct 2022 Asymptotics of cross-validation Nick Kissel
  • 04 Oct 2022 A regret-variance tradeoff in online learning Neil Xu
  • 27 Sep 2022 Minimax estimation of nonsmooth functionals Tudor Manole
  • 20 Sep 2022 E-backtesting Ruodu Wang
  • Spring 2022

  • 28 Apr 2022 Divided Differences, Falling Factorials, and Discrete Splines (Another Look at Trend Filtering and Related Problems) Part 2 Ryan Tibshirani
  • 14 Apr 2022 The Statistical Complexity of Interactive Decision Making Ojash Neopane
  • 07 Apr 2022 Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization Yusha Liu
  • 31 Mar 2022 Against theory-motivated data collection in sciences Marina Dubova
  • 24 Mar 2022 Estimating functions of bounded variation with scattered data Addison Hu
  • 24 Feb 2022 Data blurring: sample splitting a single sample James Leiner
  • 17 Feb 2022 Post-selection inference for e-value based confidence intervals Neil Xu
  • 10 Feb 2002 Catoni-style confidence sequences for heavy-tailed mean estimation. Hongjian Wang
  • Fall 2021

  • 09 Dec 2021 Schrödinger bridge generative models Andrew Warren
  • 18 Nov 2021 Fully-Adaptive Composition in Differential Privacy Justin Whitehouse
  • 11 Nov 2021 Tree-Form Sequential Decision Making Gabriele Farina
  • 04 Nov 2021 Markdown Pricing Under Unknown Demand Model Su Jia
  • 28 Oct 2021 Variable Selection and Forecasting in High Dimensional Linear Regressions with Parameter Instability Mahrad Sharifvaghefi
  • 21 Oct 2021 Strategic hypothesis testing and making forecasts that are calibrated for arbitrary data sequences Chirag Gupta
  • 14 Oct 2021 Comparing Sequential Forecasters YJ Choe
  • 07 Oct 2021 Estimating means of bounded random variables by betting Ian Waudby-Smith
  • 30 Sep 2021 Divided Differences, Falling Factorials, and Discrete Splines (Another Look at Trend Filtering and Related Problems) Ryan Tibshirani
  • 16 Sep 2021 Sequential prediction under log-loss and misspecification Shubanshu Shekar
  • 09 Sep 2021 Adaptive Sampling for Convex Regression Ojash Neopane
  • Spring 2020

  • 3 Mar 2020 Understanding the distribution of the Lasso and its applications Yuting Wei
  • 25 Feb 2020 Entry-wise perturbation bounds for eigenvectors Kevin Lin
  • 18 Feb 2020 Learning Minimax Estimators via Online Learning Arun Sai Suggala
  • 11 Feb 2020 Causal Clustering Kwahangho Kim
  • 4 Feb 2020 The Asymptotic Distribution of the MLE in High-dimensional Logistic Models Beomjo Park
  • 28 Jan 2020 Classification accuracy as a proxy for two-sample testing Ilmun Kim
  • 21 Jan 2020 Model-Independent Detection of New Physics Signals Using Semi-Supervised Classifier Tests Purvasha Chakravarti
  • 14 Jan 2020 Universal inference using the split likelihood ratio test Larry Wasserman
  • 14 January 2020 🎉 SMLRG Tin Anniversary Celebrations 🎉 SMLRG

  • Fall 2019

  • 03 Dec 2019 Non-asymptotic sequential test for overlapping hypotheses Jaehyeok Shin
  • 19 Nov 2019 Anytime-valid inference Aaditya Ramdas
  • 12 Nov 2019 Safe testing Boyan Duan
  • 05 Nov 2019 Continuum approximations for wide neural networks and gradient descent Andrew Warren
  • 29 Oct 2019 The Simulator: Understanding Adaptive Sampling in the Moderate Confidence Regime Ojash Neopane
  • 22 Oct 2019 An explanation for random forest success Lucas Mentch
  • 15 Oct 2019 Relaxing smoothness assumptions in nonparametric goodness-of-fit testing problems Alden Green
  • 08 Oct 2019 Knockoffs and the model-X framework for high-dimensional variable selection Gene Katsevich
  • 01 Oct 2019 On testing for biases in peer review Ivan Stelmakh
  • 24 Sep 2019 Understanding Langevin Diffusions Beyond Log-Concavity Andrej Risteski
  • 17 Sep 2019 Average-Case Algorithm Design Using Sum-of-Squares Pravesh Kothari
  • 10 Sep 2019 A projection-free algorithm for constrained optimization problems, with application to sparse PCA Yixuan Qiu
  • 03 Sep 2019 Benign overfitting in linear regression Pratik Patil

  • Spring 2019

  • 07 May 2019 An informal discussion of robust mean estimation Sivaraman Balakrishnan
  • 30 Apr 2019 How to choose a loss function (via an axiomatic approach; for a certain problem) Nihar Shah
  • 16 Apr 2019 Minimax conditional independence testing Matey Neykov
  • 09 Apr 2019 Robust prediction set estimation Pratik Patil
  • 02 Apr 2019 Linear regression A to W Arun Kumar Kuchibhotla
  • 26 Mar 2019 Understanding generalization in kernel ridgeless regression Pratik Patil
  • 19 Mar 2019 There exist interpolation methods with optimal/near-optimal prediction risk under noise Veeranjaneyulu Sadhanala
  • 05 Mar 2019 Some surprises in high-dimensional least squares interpolation Ryan Tibshirani
  • 26 Feb 2019 Asymptotic distributions and rates of convergence for random forests and other resampled ensemble learners Wei Pang
  • 19 Feb 2019 Can we trust the bootstrap in high-dimension? Jing Lei
  • 12 Feb 2019 Ensemble learners, exchangeability, and permutation tests Tim Coleman
  • 05 Feb 2019 Density estimation under Huber’s contamination models Zhao Ren
  • 29 Jan 2019 Being robust (in high dimensions) can be practical Adarsh Prasad
  • 22 Jan 2019 Quantile regression for big data with small memory Xi Chen
  • 15 Jan 2019 The power of online thinning in reducing discrepancy Aaditya Ramdas

  • Fall 2018

  • 04 Dec 2018 Robust estimation of mixing measures in finite mixture models Tudor Manole
  • 20 Nov 2018 Active learning and the optimal decision tree problem Su Jia
  • 13 Nov 2018 Linear-time TV denoising on graphs; trend filtering and discrete derivatives Ryan Tibshirani
  • 16 Oct 2018 A continuous-time view of early stopping for least squares regression Alnur Ali
  • 09 Oct 2018 Marchenko-Pastur asymptotics and the limiting risk of ridge regression Ryan Tibshirani
  • 02 Oct 2018 On file-drawer problems and estimation with truncated data Asaf Weinstein
  • 25 Sep 2018 Online learning, probabilistic inequalities, and the burkholder method Dylan Foster
  • 18 Sep 2018 Uniform, nonparametric, non-asymptotic confidence sequences Steven Howard
  • 11 Sep 2018 Why adaptively collected data have negative bias and how to correct for it Jaehyeok Shin
  • 04 Sep 2018 Exponential line-crossing inequalities Aaditya Ramdas
  • 22 Aug 2018 Accelerating Stochastic Gradient Descent Prateek Jain

  • Spring 2018

  • 30 May 2018 A pliable lasso Rob Tibshirani
  • 08 Mar 2018 Statistical and optimization perspectives on GANs Sivaraman Balakrishnan
  • 01 Mar 2018 GAN tutorial Biswajit Paria
  • 15 Feb 2018 Nonparametric regression with comparisons: escaping the curse of dimensionality with ordinal information Yichong Xu
  • 01 Feb 2018 Stochastic optimization of smooth functions: local minimax rates Yining Wang
  • 18 Jan 2018 Statistical inference for model parameters with stochastic gradient descent Yu-Xiang Wang

  • Fall 2017

  • 30 Nov 2017 Best subset selection vs lasso Ryan Tibshirani
  • 16 Nov 2017 Sequential selective estimation (Gaussian adaptive data analysis) and linear bandits Yu-Xiang Wang
  • 09 Nov 2017 Network embeddings and models with hyperbolic geometry Jisu Kim
  • 02 Nov 2017 Recent advances in robust estimation for the Huber's \epsilon contamination model Simon Du
  • 26 Oct 2017 Bayesian dynamic regression trees Simon Wilson
  • 19 Oct 2017 Random closed sets and their expectations Jaehyeok Shin
  • 12 Oct 2017 A new "permutation-based" look at noisy non-negative matrix completion Nihar Shah
  • 02 Oct 2017 Philosophy of science, principled statistical inference, and data science Todd Kuffner
  • 26 Sep 2017 Asymptotics of objective functionals in semi-supervised learning Dejan Slepcev
  • 19 Sep 2017 Locating the minimum of a function from adaptive queries Yining Wang
  • 12 Sep 2017 Property testing in high dimensional Ising models Matey Neykov
  • 05 Sep 2017 Depth-based nonparametric tests for homogeneity of functional data Gery Geenens
  • 16 Aug 2017 Active learning for cost sensitive classification Akshay Krishnamurthy

  • Spring 2017

  • 03 May 2017 Solving SDPs for synchronization and MaxCut problems via the Grothendieck inequality Dave Choi
  • 19 Apr 2017 Some theoretical results on Thompson sampling for Multi-armed Bandits Kirthevasan Kandasamy
  • 12 Apr 2017 A statistician walks into a deep learning bar… YJ Choe
  • 05 Apr 2017 Cross-Validation with Confidence Jing Lei
  • 29 Mar 2017 How many units of blood will the Stanford Hospital need tomorrow? Rob Tibshirani
  • 22 Mar 2017 On the power of truncated SVD for general high-rank matrix estimation problems Yining Wang
  • 03 Mar 2017 Double machine learning for treatment and causal parameters Edward Kennedy
  • 22 Feb and 01 Mar 2017 Exact post-selection inference with the generalized lasso Justin Hyun
  • 08 Feb 2017 Learning high-dimensional structural equation models Bryon Aragam
  • 01 Feb 2017 Towards practical machine learning with differential privacy and beyond Yu-Xiang Wang
  • 25 Jan 2017 Geometry of the space of phylogenetic trees and their limiting behaviors Jisu Kim
  • 18 Jan 2017 Total variation classes beyond 1d: minimax rates, and the limitations of linear smoothers Veeranjaneyulu Sadhanala

  • Fall 2016

  • 13 Dec 2016 Excess optimism, or: what is the prediction error of an estimator tuned by SURE? Ryan Tibshirani
  • 06 Dec 2016 Error bounds for spectral convergence of empirical graph Laplacians Dejan Slepcev
  • 29 Nov 2016 Estimating whole brain dynamics using spectral clustering Yi Yu
  • 15 Nov 2016 Computationally tractable selection of experiments in regression models Yining Wang
  • 08 Nov 2016 A remark on cross-validation for sparse reduced rank models Yiyuan She
  • 01 Nov 2016 Higher order influence functions and minimax estimation of nonlinear functionals James Robins
  • 25 Oct 2016 Indirect Gaussian graph learning beyond Gaussianity Yiyuan She
  • 18 Oct 2016 Statistical matching with latent variable models Will Bishop
  • 11 Oct 2016 Sketching meets random projection in the dual: a provable recovery algorithms for big and high-dimensional data Mladen Kolar
  • 04 Oct 2016 Discovery and visualization of nonstationary causal models Kun Zhang
  • 27 Sep 2016 Contextual bandit and off-policy evaluation: minimax bounds and new algorithm Yu-Xiang Wang
  • 20 Sep 2016 Nonparametric methods for doubly robust estimation of continuous treatment effects Edward Kennedy
  • 13 Sep 2016 Goodness of fit tests for high-dimensional linear models Rajen Shah
  • 06 Sep 2016 Statistical inference with random forests Lucas Mentch

  • Spring 2016

  • 25 Apr 2016 A Grothendieck-type inequality for local maxima Dave Choi
  • 18 Apr 2016 Algorithmic and statistical perspectives of randomized sketching for ordinary least-squares Garvesh Raskutti
  • 11 Apr 2016 Graph sparsification approaches for laplacian smoothing Veeranjaneyulu Sadhanala
  • 4 Apr 2016 Doubly stochastic primal-dual coordinate method for empirical risk minimization Adams Wei Yu
  • 28 Mar 2016 Sample complexity of episodic fixed-horizon reinforcement learning Christoph Dann
  • 21 Mar 2016 Post-regularization inference for dynamic nonparanormal graphical models Mladen Kolar
  • 14 Mar 2016 Near-optimal minimax subsampling for low-dimensional linear regression Yining Wang
  • 22 Feb 2016 The multi-fidelity bandit Kirthevasan Kandasamy
  • 15 Feb 2016 Latent variable modeling with diversity-inducing mutual Angular Regularization Pengtao Xie
  • 8 Feb 2016 Active search for sparse signals with region sensing Yifei Ma
  • 1 Feb 2016 Algebraic geomtry for the resolution of singularities to singular models Jisu Kim
  • 25 Jan 2016 Internal inference Rob Tibshirani
  • 18 Jan 2016 Minimax theory for ranking from pairwise comparisons Sivaramam Balakrishnan
  • 11 Jan 2016 Understanding adaptive data analysis Yu-Xiang Wang

  • Fall 2015

  • 02 Dec 2015 Topics in differential private machine learning Yu-Xiang Wang
  • 1 Dec 2015 Optimal rates for the random Fourier feature method Zoltan Szabo
  • 25 Nov 2015 The limit of U-Statistic based nonparametric test for conditional independence Kacper Chawialkowski
  • 18 Nov 2015 On online control of false discovery rate Kirthevasan Kandasamy
  • 11 Nov 2015 Covariance sketching: leveraging structure to estimate covariance matrices from compressed samples Gautam Dasarathy
  • 4 Nov 2015 Asymptotic theory for density ridges Yen-Chi Chen
  • 28 October 2015 Generalization in adaptive data analysis and holdout reuse Larry Wasserman
  • 21 October 2015 Graph-guided banding for covariance estimation Jacob Bien
  • 14 October 2015 Random networks, exchangeability and graphical models Alessandro Rinaldo
  • 7 October 2015 Bootstrap techniques for massive data Jing Lei
  • 30 September 2015 An overview of subsampling in linear regression Aarti Singh
  • 23 September 2015 Reach, medial axis, and their stability Jisu Kim
  • 16 September 2015 Simplicial manifold reconstruction via tangent space estimation Eddie Aamari
  • 9 September 2015 Random projection ensemble classification Ryan Tibshirani

  • Spring 2015

  • 19 June 2015 Sequential nonparametric testing with the law of the iterated logarithm Aaditya Ramdas
  • 23 April 2015 Some progress on structured normal means inference Akshay Krishnamurthy
  • 16 April 2015 Statistical inference for topological data analysis Fabrizio Lecci
  • 09 April 2015 Orbit regularization Ranato Negrinho
  • 02 April 2015 Comparing whole-space clusterings Jose Chacon
  • 26 March 2015 Distribution-free transportation-based two sample test Nicolas Garcia Trillos
  • 19 March 2015 Stability theorem for persistent homology Jisu Kim
  • 26 February 2015 A general framework for fast stagewise algorithms Ryan Tibshirani
  • 19 February 2015 All of two sample testing Aaditya Ramdas
  • 12 February 2015 GP bandits Kirthevasan Kandasamy
  • 05 February 2015 A "rant" on assumptions Larry Wasserman
  • 29 January 2015 Nonparametric modal regression Yen-Chi Chen
  • 22 January 2015 Stochastic blockmodels, graphons and K-means clustering Dave Choi

  • Fall 2014

  • 04 Dec 2014 Some elements of mathematical phylogenetics Gautam Dasarathy
  • 20 Nov 2014 Nonparametric estimation of smooth functionals of densities Kirthevasan Kandasamy
  • 13 Nov 2014 Intriguing properties of deep neural networks Cosma Shalizi
  • 06 Nov 2014 Subspace clustering Yu-Xiang Wang
  • 30 Oct 2014 Recent results in multi-Class learnability Ruth Urner
  • 04 Sep 2014 Two sample testing in high dimensions Aaditya Ramdas
  • 09 Oct 2014 Sparse PCA continued Jing Lei
  • 02 Oct 2014 Sparse PCA Jing Lei
  • 25 Sep 2014 What regularized auto-encoders learn from the data generating distribution Ryan Tibshirani
  • 18 Sep 2014 Deep learning: an implementation Kevin Lin
  • 11 Sep 2014 Convolutional neural networks and dropout Amir-Massoud Farahmand
  • 04 Sep 2014 Introduction to deep learning Rob Tibshirani

  • Spring 2014

  • 24 Apr 2014 Collective stability in structured prediction: generalization from one example Cosma Shalizi
  • 17 Apr 2014 Differential privacy Yu-Xiang Wang
  • 10 Apr 2014 Continuum limit of total variation on point clouds Nicolas Garcia Trillos
  • 03 Apr 2014 High-dimensional covariance estimation Aaditya Ramdas
  • 27 Mar 2014 Density functional estimation Barnabas Poczos
  • 20 Mar 2014 On robust regression with high-dimensional predictors Jing Lei
  • 06 Mar 2014 Degrees of freedom and model search Ryan Tibshirani
  • 27 Feb 2014 Stein's method for concentration inequalities Alessandro Rinaldo
  • 20 Feb 2014 A CLT and tight lower bounds for estimating entropy Akshay Krishnamurthy
  • 13 Feb 2014 Stein's method; part II (section 12 onwards) Larry Wasserman
  • 06 Feb 2014 Stein's method; section 7 Larry Wasserman
  • 30 Jan 2014 Stein's method; sections 4, 5, 6, 8 Larry Wasserman
  • 23 Jan 2014 Stein's method; sections 1-3 Larry Wasserman
  • 16 Jan 2014 Persistent homology Fabrizio Lecci

  • Fall 2013

  • 20 Nov 2013 Confidence intervals and hypothesis testing for high-dimensional regression Aaditya Ramdas
  • 13 Nov 2013 Sum of squares graphical models Zico Kolter
  • 06 Nov 2013 Mean-shift algorithms for clustering and manifold denoising Miguel Carreira Perpinan
  • 30 Oct 2013 Fantope projection and selection: near-optimal convex relaxation of sparse PCA Jing Lei
  • 20 Nov 2013 Confidence intervals and hypothesis testing for high-dimensional regression Aaditya Ramdas
  • 23 Oct 2013 Almost surely something fun! Rob Tibshirani
  • 16 Oct 2013 A bandit tour of sequential decision making Aaditya Ramdas
  • 09 Oct 2013 Normal means over planted clique graphs Akshay Krishnamurthy
  • 02 Oct 2013 High-dimensional bootstrap Larry Wasserman
  • 25 Sep 2013 Uniform rates of convergence for k-means and (some) Gaussian mixtures Matus Telgarsky
  • 18 Sep 2013 Breakpoint detection of nonstationary time series using wild binary segmentation Karolos Korkas
  • 11 Sep 2013 Persistent statbility for geometric complexes Frederic Chazal

  • Spring 2013

  • 18 Apr 2013 Computational lower bounds for sparse PCA Mladen Kolar
  • 11 Apr 2013 A significance test for the lasso Ryan Tibshirani
  • 04 Apr 2013 Learning theory estimates via integral operators and their approximations Ina Fiterau
  • 28 Mar 2013 Computational and statistical tradeoffs via convex relaxation Sohail Bahmani
  • 21 Mar 2013 Second order comparison of Gaussian random functions and the geometry of DNA minicircles Jing Lei
  • 07 Mar 2013 Topological ideas in computer science Amir Nayyeri
  • 28 Feb 2013 Metric graph reconstruction from noisy data Fabrizio Lecci
  • 21 Feb 2013 Spectral clustering based on local PCA Akshay Krishnamurthy
  • 14 Feb 2013 Robust kernel density estimation Martin Azizyan
  • 07 Feb 2013 Wigner's semicircle law and random matrix theory James Sharpnack
  • 31 Jan 2013 A framework for estimation of convex functions Aarti Singh
  • 24 Jan 2013 Game theory, mechanism design, and connections to statistics Min Xu
  • 17 Jan 2013 Almost surely something fun! Xi Chen

  • Fall 2012

  • 03 Dec 2012 Convex analysis and optimization with submodular functions: a tutorial James Sharpnack
  • 26 Nov 2012 Almost surely something fun! Daniella Witten
  • 19 Nov 2012 Bayesian models for record linkage Rebecca Steorts
  • 12 Nov 2012 Optimal rates of convergence for estimating toeplitz covariance matrices Sohail Bahmani
  • 05 Nov 2012 Confidence sets in sparse regression Ina Fiterau
  • 29 Oct 2012 Privacy aware learning Akshay Krishnamurthy
  • 22 Oct 2012 Shapes of Gaussian mixture models Brittany Fasy
  • 15 Oct 2012 Learning bounds for importance weighting Cosma Shalizi
  • 08 Oct 2012 Pairwise variable selection for high-dimensional model-based clustering Martin Azizyan
  • 01 Oct 2012 Correlated variables in regression: clustering and sparse estimation Mladen Kolar
  • 24 Sep 2012 Challenge problem Ryan Tibshirani
  • 17 Sep 2012 Connections between logic and probability, random SAT instances and phase transitions Aaditya Ramdas
  • 10 Sep 2012 Optimal stochastic convex optimization through the lens of active learning Aaditya Ramdas

  • Spring 2012

  • 26 Mar 2012 The lasso, correlated design, and improved oracle inequalities Mladen Kolar
  • 19 Mar 2012 A geometric analysis of subspace clustering with outliers Sivaramam Balakrishnan
  • 05 Mar 2012 On low-dimensional projections of high-dimensional distributions Martin Azizyan
  • 27 Feb 2012 Tight conditions for consistent variable selection in high dimensional nonparametric regression Ian Fiterau
  • 20 Feb 2012 Lower bounds for passive and active learning Steve Hanneke
  • 13 Feb 2012 Noisy independent factor analysis model for density estimation and classification Larry Wasserman
  • 06 Feb 2012 Variance estimation using refitted cross-validation in ultrahigh dimensional regression James Sharpnack
  • 30 Jan 2012 Simpler approach to matrix completion Aaditya Ramdas
  • 23 Jan 2012 Minimax rates of estimation for sparse PCA in high dimensions Vince Vu

  • Fall 2011

  • 17 Nov 2011 Approximation of functions of few variables in high dimensions Ina Fiterau
  • 10 Nov 2011 Almost surely something fun! James Sharpnack
  • 03 Nov 2011 Almost surely something fun! Martin Azizyan
  • 27 Oct 2011 Cross validation is risk consistent for lasso Barren Homrighausen and Dan McDonald
  • 20 Oct 2011 Almost surely something fun! Rob Tibshirani
  • 06 Oct 2011 High-dimensional regression with noisy and missing data: provable guarantees with non-convexity Akshay Krishnamurthy
  • 22 Sep 2011 Spectral methods for learning multivariate latent tree structure Ankur Parikh
  • 15 Sep 2011 Calibrated forecasters Aaditya Ramdas
  • 08 Sep 2011 Neyman-Pearson classification, convexity and stochastic constraints Sivaraman Balakrishnan
  • 01 Sep 2011 The benefit of group sparsity Min Xu

  • Spring 2011

  • 20 Apr 2011 Empirical risk minimization in inverse problems Darren Homrighausen
  • 30 Mar 2011 High-dimensional analysis of semidefinite relaxations for sparse principal components Mladen Kolar
  • 23 Mar 2011 Online learning Aaditya Ramdas
  • 16 Mar 2011 Dynamics of Bayesian updating with dependent data and misspecified models Cosma Shalizi
  • 04 Mar 2011 Noisy matrix decomposition via convex relaxation: optimal rates in high dimensions Alekh Agarwal
  • 23 Feb 2011 Information theoretic model validation for clustering Larry Wasserman
  • 16 Feb 2011 Nuclear norm penalization and optimal rates for noisy low rank matrix completion Akshay Krishnamurthy
  • 09 Feb 2011 Stability bounds for stationary phi-mixing and beta-mixing processes Dan McDonald
  • 02 Feb 2011 Concentration inequalities of the cross-validation estimate for stable predictors Martin Azizyan
  • 26 Jan 2011 The sample complexity of dictionary learning Min Xu
  • 21 Jan 2011 Detection of an anomalous cluster in a network James Sharpnack
  • 14 Jan 2011 High dimensional structure learning of ising models on sparse random graphs Divyanshu Vats

  • Fall 2010

  • 17 Nov 2010 Distribution-specific agnostic boosting Steve Hanneke
  • 10 Nov 2010 Rates of convergence for the cluster tree Sivaramam Balakrishnan
  • 03 Nov 2010 Implementing regularization implicitly via approximate eigenvector computation Shiva Kaul
  • 27 Oct 2010 SPADES and mixture models Darren Warren Homrighausen
  • 13 Oct 2010 A new analysis of co-training Martin Azizyan
  • 06 Oct 2010 A framework for feature selection in clustering Larry Wasserman
  • 29 Sep 2010 Learning latent tree graphical models Akshay Krishnamurthy
  • 22 Sep 2010 Spectral clustering based on local linear approximations James Sharpnack
  • 15 Sep 2010 Latent variable graphical model selection via convex optimization Aarti Singh
  • 08 Sep 2010 Lossy source compression using low-density generator matrix codes: analysis and algorithms Min Xu
  • 01 Sep 2010 VC bounds on the cardinality of nearly orthogonal function classes Shiva Kaul

  • 2009-2010

  • 2009-2010 And there was once a beginning!

Machine Learning Department & Statistics Department at Carnegie Mellon University

Based on the UW Sampa group website