Fall 2018

Sep 7Dejan Slepcev (CMU)
Varational problems on random structures and their continuum limits
E18-304, 11am – 12pm
Sep 14Gregory Wornell (MIT)
An information-Geometric View of Learning in High Dimensions
E18-304, 11am – 12pm
Sep 21Boaz Nadler (Weizmann Institute)
Unsupervised Ensemble Learning
E18-304, 11am – 12pm
Sep 28Jingbo Liu (MIT)
Reverse hypercontractivity beats measure concentration for information theoretic converses
E18-304, 11am – 12pm
Oct 5Tselil Schramm (Harvard University)
Efficient Algorithms for the Graph Matching Problem in Correlated Random Graphs
E18-304, 11am – 12pm
Oct 12John Duchi (Stanford University)
Locally private estimation, learning, inference, and optimality
E18-304, 11am – 12pm
Oct 19Aukosh Jagannath (Harvard)
Algorithmic thresholds for tensor principle component analysis
E18-304, 11am – 12pm
Oct 26Alan Frieze (Carnegie Mellon University)
On the cover time of two classes of graph
E18-304, 11am – 12pm
Nov 2Sumit Mukherjee (Columbia University)
Joint estimation of parameters in Ising Model
E18-304, 11am – 12pm
Nov 9Zongming Ma (University of Pennsylvania)
Optimal hypothesis testing for stochastic block models with growing degrees
E18-304, 11am – 12pm
Nov 16Lucas Janson (Harvard University)
Model-X knockoffs for controlled variable selection in high dimensional nonlinear regression
E18-304, 11am – 12pm
Nov 30Vladimir Koltchinskiib (Georgia Tech)
Bias Reduction and Asymptotic Efficiency in Estimation of Smooth Functionals of High-Dimensional Covariance
E18-304, 11am – 12pm
Dec 7Guy Bresler (MIT)
Reducibility and Computational Lower Bounds for Some High-dimensional Statistics Problems
E18-304, 11am – 12pm
Dec 14Lutz Warnke (Georgia Tech)
Large girth approximate Steiner triple systems
E18-304, 11am – 12pm

Spring 2018

Feb 2Sahand Negahban (Yale)
Connections between structured estimation and weak submodularity
E18-304, 11am – 12pm
Feb 9Garvesh Raskutti (Wisconsin)
Variable selection using presence-only data with applications to biochemistry
E18-304, 11am – 12pm
Feb 16Arnak Dalalyan CREST (Paris)
User-friendly guarantees for the Langevin Monte Carlo
E18-304, 11am – 12pm
Feb 23Nathan Srebro-Bartom (TTI-Chicago)
Optimization’s Implicit Gift to Learning: Understanding Optimization Bias as a Key to Generalization
E18-304, 11am – 12pm
Mar 2Alexandra Carpentier (Potsdam)
One and two sided composite-composite tests in Gaussian mixture models
E18-304, 11am – 12pm
Mar 9Afonso Bandeira (NYU)
Statistical estimation under group actions: The Sample Complexity of Multi-Reference Alignment
E18-304, 11am – 12pm
Mar 16David Sontag (MIT)
When Inference is tractable
E18-304, 11am – 12pm
Mar 23Johannes Schmidt Hieber (Leiden)
Statistical theory for deep neural networks with ReLU activation function
E18-304, 11am – 12pm
Apr 6Jianqing Fan (Princeton)
Optimality of Spectral Methods for Ranking, Community Detections and Beyond 
E18-304, 11am – 12pm
Apr 13Subrabatha Sen (Microsoft)
Testing degree corrections in Stochastic Block Models
E18-304, 11am – 12pm
Apr 27Genevera Allen (Rice)
Inference, Computation, and Visualization for Convex Clustering and Biclustering
E18-304, 11am – 12pm
May 4Ohad Shamir (Weizman)
Size-Independent Sample Complexity of Neural Networks
E18-304, 11am – 12pm
May 11Adel Javanmard (USC)
Dynamic Incentive-aware Learning: Robust Pricing in Contextual Auctions
E18-304, 11am – 12pm
May 25Hariharan Narayanan (MIT/UW)
Fitting a putative manifold to noisy data
E18-304, 11am – 12pm

Fall 2017

Sep 8Andrej Risteski (Princeton University)
New provable techniques for learning and inference in probabilistic graphical models
E18-304, 11am – 12pm
Sep 15Yury Polyanskiy (MIT)
Sample complexity of population recovery
E18-304, 11am – 12pm
Sep 22Amir Dembo (Stanford University)
Walking within growing domains: recurrence versus transience
E18-304, 11am – 12pm
Sep 29Jelani Nelson (Harvard University)
Optimal lower bounds for universal relation, and for samplers and finding duplicates in streams
E18-304, 11am – 12pm
Oct 6Youssef Marzouk (MIT)
Transport maps for Bayesian computation
E18-304, 11am – 12pm
Oct 13Galen Reeves (Duke University)
Additivity of Information in Deep Generative Networks: The I-MMSE Transform Method
E18-304, 11am – 12pm
Oct 19John Cunningham (Columbia)
Structure in multi-index tensor data: a trivial byproduct of simpler phenomena?
E18-304, 11am – 12pm
Oct 20Sayan Mukherjee (Duke)
Inference in dynamical systems and the geometry of learning group actions
E18-304, 11am – 12pm
Oct 27Amit Daniely (Google)
On Learning Theory and Neural Networks
E18-304, 11am – 12pm
Nov 1Pierre Jacob (Harvard)
Unbiased Markov chain Monte Carlo with couplings
E18-304, 11am – 12pm
Nov 3Joan Bruna Estrach (NYU)
Statistics, Computation and Learning with Graph Neural Networks
E18-304, 11am – 12pm
Nov 17Alex Dimakis (University of Texas at Austin)
Generative Models and Compressed Sensing
E18-304, 11am – 12pm
Dec 1Susan Murphy (Harvard University)
Challenges in Developing Learning Algorithms to Personalize Treatment in Real Time
E18-304, 11am – 12pm
Dec 8Alex Bloemendal (Broad Institute)
Genome-wide association, phenotype prediction, and population structure: a review and some open problems
E18-304, 11am – 12pm

Spring 2017

Feb 3 Mayya Zhilova (Georgia Tech)
Non-classical Berry-Esseen inequality and accuracy of the weighted bootstrap
E18-304, 11am – 12pm
Feb 10 Pierre Bellec (Rutgers)
Slope meets Lasso in sparse linear regression
E18-304, 11am – 12pm
Feb 17Frederick Eberhardt (CalTech)
Causal Discovery in Systems with Feedback Cycles
E18-304, 11am – 12pm
Feb 24Yihong Wu (Yale)
Estimating the number of connected components of large graphs based on subgraph sampling
E18-304, 11am – 12pm
Mar 3Alexander Barvinok (University of Michigan)
Computing partition functions by interpolation
E18-304, 11am – 12pm
Mar 10Ankur Moitra (MIT)
Robust Statistics, Revisited
E18-304, 11am – 12pm
Mar 17David Dunson (Duke)
Probabilistic factorizations of big tables and networks
32-141, 11am – 12pm
Mar 24Shankar Bhamidi (UNC)
Jagers-Nerman stable age distribution theory, change point detection and power of two choices in evolving networks
E18-304, 11am – 12pm
Apr 7David Steurer (Cornell)
Sample-optimal inference, computational thresholds, and the methods of moments
E18-304, 11am – 12pm
Apr 14Daniel Hsu (Columbia)
Active learning with seed examples and search queries
E18-304, 11am – 12pm
Apr 28Ronitt Rubinfeld (MIT)
Testing properties of distributions over big domains
32-141, 11am – 12pm
May 5 Sebastien Roch (Wisconsin)
Some related phase transitions in phylogenetics and social network analysis
E18-304, 11am – 12pm
May 12 Jonas Peters (University of Copenhagen)
Invariance and Causality
E18-304, 11am – 12pm
May 19 Vianney Perchet (ENS Paris-Saclay)
Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe
E18-304, 11am – 12pm

Fall 2016

Sep 9Pierre Jacob (Harvard)
Couplings of Particle Filters
E18-304, 11am – 12pm
Sep 16Lorenzo Rosasco (University of Genoa)
Less is more: optimal learning by subsampling and regularization
E18-304, 11am – 12pm
Sep 30Bin Yu (UC Berkeley)
Theory to gain insight and inform practice: re-run of IMS Rietz Lecture, 2016
E18-304, 11am – 12pm
Oct 7Mark Rudelson (University of Michigan)
Invertibility and Condition Number of Sparse Random Matrices
E18-304, 11am – 12pm
Oct 14Mikhail Belkin (Ohio State University)
Eigenvectors of Orthogonally Decomposable Functions and Applications
E18-304, 11am – 12pm
Oct 21Arian Maleki (Columbia)
On The Asymptotic Performance of fq-regularized Least Squares
E18-304, 11am – 12pm
Oct 28Sourav Chatterjee (Stanford)
Matrix estimation by Universal Singular Value Thresholding
E18-304, 11am – 12pm
Nov 4Po-Ling Loh (University of Pennsylvania)
Influence maximization in stochastic and adversarial settings
E18-304, 11am – 12pm
Nov 18Liza Levina (University of Michigan)
Interpretable prediction models for network-linked data
E18-304, 11am – 12pm
Dec 2Elchanan Mossel (MIT)
Shotgun Assembly of Graphs
E18-304, 11am – 12pm
Dec 16Yash Deshpande (Microsoft Research)
Sparse PCA via covariance thresholding
E18-304, 11am – 12pm

Spring 2016

Feb 5Andrew Nobel (UNC)
Large Average Submatrices of a Gaussian Random Matrix: Landscapes and Local Optima
32-123, 11am – 12pm
Feb 12David Donoho (Stanford)
Incremental Methods for Additive Convex Cost Optimization
32-123, 11am – 12pm
Feb 19Asu Ozdaglar (MIT)
Overcoming Overfitting with Algorithmic Stability
32-123, 11am – 12pm
Feb 26John Lafferty (U Chicago)
On Shape Constrained Estimation
E18-304, 11am – 12pm
Mar 4Shivani Agarwal (Indian Institute of Science/Radcliffe)
On Complex Supervised Learning Problems, and On Ranking and Choice Models
32-123, 11am – 12pm
Mar 18Martin Wainwright (UC Berkeley)
Pairwise Comparison Models for High-Dimensional Ranking
32-123, 11am – 12pm
Apr 1Roberto Oliveira (IMPA)
Sub-Gaussian Mean Estimators
32-123, 11am – 12pm
Apr 8 Tony Cai (U Penn)
Confidence Intervals for High-Dimensional Linear Regression: Minimax Rates and Adaptivity
32-123, 11am – 12pm
Apr 15Gabor Szekely (NSF)
The Energy of Data
32-123, 11am – 12pm
Apr 22Ryan Tibshirani (Carnegie Mellon)
Recent Advances in Trend Filtering
32-123, 11am – 12pm
Apr 29Victor Chernozhukov (MIT)
Double Machine Learning: Improved Point and Interval Estimation of Treatment and Causal Parameters
32-123, 11am – 12pm
May 6Rachel Ward (UT Austin)
Extracting Governing Equations in Chaotic Systems From Highly Corrupted Data
32-123, 11am – 12pm
May 13David Blei (Columbia)
Scaling and Generalizing Variational Inference
32-123, 11am – 12pm

Fall 2015

Sep 11Rob Freund (MIT Sloan)
An Extended Frank-Wolfe Method with Application to Low-Rank Matrix Completion
32-141, 11am-12pm
Sep 18Mustazee Rahman (MIT Mathematics)
Independent sets, local algorithms and random regular graphs
32-141, 11am-12pm
Sep 25Edo Airoldi (Harvard University)
Some Fundamental Ideas for Causal Inference on Large Networks
32-141, 11am-12pm
Oct 2Constantine Caramanis (University of Texas at Austin)
Fast algorithms and (other) min-max optimal algorithms for mixed regression
32-141, 11am-12pm
Oct 9Roman Vershynin (University of Michigan)
Discovering hidden structures in complex networks
32-141, 11am-12pm
Oct 16Stefan Wager (Stanford University)
Causal Inference with Random Forests
32-141, 11am-12pm
Oct 23Robert Nowak (University of Wisconsin)
Ranking and Embedding From Pairwise Comparisons
32-141, 11am-12pm
Oct 30Rina Foygel Barber (University of Chicago)
MOCCA: a primal/dual algorithm for nonconvex composite functions with applications to CT imaging
32-141, 11am-12pm
Nov 6Gábor Lugosi (Pompeu Fabra University)
On a High-Dimensional Random Graph Process
32-141, 11am-12pm
Nov 13Jun Liu (Harvard University)
Expansion of biological pathways by integrative Genomics
32-141, 11am-12pm
Nov 20James Robins (Harvard University)
Minimax Estimation of Nonlinear Functionals with Higher Order Influence Functions: Results and Applications
32-141, 11am-12pm
Dec 4Eric Tchetgen Tchetgen (Harvard University)
Next Generation Missing Data Methodology
32-141, 11am-12pm
Dec 11Peter Bartlett (UC Berkeley)
Efficient Optimal Strategies for Universal Prediction
32-141, 11am-12pm

Spring 2015

Feb 6Denis Chetverikov (UCLA)
Central Limit Theorems and Bootstrap in High Dimensions
E62-450, 11am-12pm
Feb 13Victor-Emmanuel Brunel (Yale)
Random polytopes and estimation of convex bodies
E17-133, 11am-12pm
Feb 27Nike Sun (MSR New England and MIT Mathematics)
The exact k-SAT threshold for large k
E62-450, 11am-12pm
Apr 10Moritz Hardt (IBM Almaden)
How good is your model? Guilt-free interactive data analysis
E62-450, 11am-12pm
Apr 17Vianney Perchet (Université Paris Diderot)
From Bandits to Ethical Clinical Trials. Optimal Sample Size for Multi-Phases Problems
E62-450, 11am-12pm
Apr 24Ankur Moitra (MIT CSAIL)
Tensor Prediction, Rademacher Complexity and Random 3-XOR
E62-450, 11am-12pm
May 1Han Liu (Princeton)
Nonparametric Graph Estimation
E62-450, 11am-12pm
May 8Lester Mackey (Stanford)
Measuring Sample Quality with Stein’s Method
E62-450, 11am-12pm

Fall 2014

Aug 15Lenka Zdeborova (CEA)
Clustering of sparse networks: Phase transitions and optimal algorithms
E62-587, 3:15pm-4:15pm
Aug 15Florent Krzakala (Université Pierre et Marie)
Superposition codes and approximate-message-passing decoder
E62-587, 2pm-3pm
Sep 23Richard Nickl (University of Cambridge)
Uncertainty quantification and confidence sets in high-dimensional models
E62-587, 12pm – 1pm
Oct 10Vladimir Koltchinskii (Georgia Tech)
Asymptotics and concentration for sample covariance
E62-650, 11am – 12pm
Oct 24Anna Mikusheva (MIT Economics)
A Geometric Approach to Weakly Identified Econometric Models
E62-687, 11am – 12pm
Oct 31Yuan Liao (University of Maryland) 
High Dimensional Covariance Matrix Estimations and Factor Models
E62-587, 11am-12pm
Nov 7Constantinos Daskalakis (MIT EECS)
Beyond Berry Esseen: Structure and Learning of Sums of Random Variables
E62-587, 11am-12pm
Nov 21Alfred Galichon (Sciences Po, Paris)
Optimal stochastic transport
E62-587, 11am-12pm
Dec 5Harrison Huibin Zhou (Yale University)
Sparse Canonical Correlation Analysis: Minimaxity and Adaptivity
E62-587, 11am-12pm
Dec 12Whitney Newey (MIT Economics)
Linear Regression with Many Included Covariates
E62-587, 11am-12pm

Spring 2014

Feb 7Michael Brautbar (MIT)
On the Power of Adversarial Infections in Networks
E62-587, 11am-12pm
Mar 7Karthekeyan Chandrasekaran (Harvard)
Integer Feasibility of Random Polytopes
E62-587, 11am-12pm
Mar 21Alexandre Tsybakov (CREST-ENSAE)
Linear and Conic Programming Approaches to High-Dimensional Errors-in-variables Models
E62-587, 11am-12pm
Apr 11Alexander Rakhlin (University of Pennsylvania, The Wharton School)
Learning and estimation: separated at birth, reunited at last
E62-587, 11am-12pm
Apr 18Sébastien Bubeck (Princeton University) 
On the influence of the seed graph in the preferential attachment model
E62-587, 11am-12pm
Apr 25Joel Spencer (Courant Institute, New York University)
Avoiding Outliers
E62-587, 11am-12pm
May 2Sahand Negahban (Yale University)
Computationally and Statistically Efficient Estimation in High-Dimensions
E62-587, 2pm-3pm
May 16Antar Bandyopadhyay (University of California, Berkeley)
De-Preferential Attachment Random Graphs
E62-587, 11am-12pm
May 23Alex Belloni (Duke University)
Uniform Post Selection Inference for Z-estimation problems
E62-587, 11am-12pm
May 30Nathan Kallus (MIT)
Regression-Robust Designs of Controlled Experiments
E62-587, 11am-12pm

Fall 2013

Sep 20Elad Hazan (Technion)
Sublinear Optimization
N/A
Sep 27Jim Dai (Cornell University)
Semimartingale reflecting Brownian motions: tail asymptotics for stationary distributions
E62-587, 11am-12pm
Nov 8David Choi (Heinz College, Carnegie Mellon University)
Consistency of Co-clustering exchangeable graph data
E62-587, 11am-12pm
Nov 13Lie Wang (MIT)
Multivariate Regression with Calibration
E62-587, 4pm-5pm
Nov 15Ramon van Handel (Princeton University)
Conditional Phenomena in Time and Space
E62-587, 11am-12pm
Dec 13Nelly Litvak (University of Twente)
Degree-degree dependencies in random graphs with heavy-tailed degrees
E62-587, 11am-12pm

Spring 2013

Feb 8Rahul Jain (University of Southern California)
The Art of Gambling in a Team: Multi-Player Multi-Armed Bandits
 
Apr 12Yashodhan Kanoria (MSR New England and Columbia University)
Which side chooses in large random matching markets?
 
May 3Rahul Jain (University of Southern California)
Transitory Queueing Systems
 

Fall 2012

Nov 30thRahul Mazumder (MIT)
Low-rank Matrix Completion: Statistical Models and Large Scale Algorithms
 
Nov 16thKuang Xu (MIT)
Queueing system topologies with limited flexibility
 
Oct 26thPhilippe Rigollet (Princeton University)
Optimal detection of a sparse principal component
 

Spring 2012

Mar 30Dmitry Shabanov (Yandex and Moscow Institute of Physics and Technology)
Van der Warden Number and Coloring of Hypergraphs with Large Girth
 
Mar 29Liudmila Ostroumova (Yandex and Moscow Institute of Physics and Technology)
An Application of Talagrand’s Inequality to Prove a Concentration of Second Degrees in Buckley-Osthus Random Graph Model
 
Mar 28Daniil Musatov (Yandex and Moscow Institute of Physics and Technology)
Conditional Coding with Limiting Computational Resources
 
Mar 27Andrei Raigorodksii (Yandex and Moscow Institute of Physics and Technology)
Web Graph Models and Their Applications
 
Mar 26Andrei Raigorodksii (Yandex and Moscow Institute of Physics and Technology)
Research Groups at Yandex and Moscow Institute of Physics and Technology
 
Apr 20Guy Bresler (University of California, Berkeley)
Information theory of DNA sequencing
 
Apr 27Alexander Rybko (Institute for Information Transmission Problems, Russia)
Mean-field Limit for General Queueing Networks on Infinite Graphs
 
Apr 27Semen Shlosman (CNRS, France and Institute for Information Transmission Problems, Russia)
The Coherence Phase Transition
 
May 18Alexei Borodin (Massachusetts Institute of Technology)
Growth of random surfaces
 

Fall 2011

Oct 7 Erol Peköz (Boston University)
Asymptotics for preferential attachment random graphs via Stein’s method
 
Oct 21Eitan Bachmat (Ben-Gurion University)
Does god play dice? An I/O scheduling and airplane boarding perspective
 
Dec 16Yuan Zhong (MIT ORC)
Delay optimality in switched networks
 

Spring 2009

Mar 13Mohsen Bayati (Microsoft Research New England)
Sequential algorithms for generating random graphs
 
Apr 3Mokshay Madiman (Yale University)
A New Look at the Compound Poisson Distribution and Compound Poisson Approximation using Entropy
 
Apr 10Scott Sheffield (MIT Math)
Fractional simple random walk
 
Apr 17Vivek F. Farias (MIT Sloan)
The Smoothed Linear Program for Approximate Dynamic Programming
 
May 1Vivek Goyal (MIT EECS)
On Resolution, Sparse Signal Recovery, and Random Access Communication
 

Fall 2008

Sep 23Benoît Collins (University of Ottawa) Convergence of unitary matrix integrals 

Spring 2008

Feb 29Victor Chernozhukov (MIT Econ & ORC)
Quantile and Probability Curves without Crossing
 
Mar 21Daron Acemoglu (MIT Economics)
Fragility of Asymptotic Agreement under Bayesian Learning
 
Apr 10Peter Glynn (Stanford MS&E)
Bounds on Stationary Expectations for Markov Processes
 
Apr 18Ton Dieker(Georgia Tech I&SE)
Large deviations for random walks under subexponentiality: the big-jump domain
 
Apr 25Edward Farhi (MIT Physics)
Quantum Computation by Adiabatic Evolution
 
May 23Johan van Leeuwaarden (Eindhoven University of Technology, EURANDOM, NYU)
The Gaussian random walk, sampling Brownian motion, and the Riemann zeta function
 

Fall 2007

Nov 16David Forney (MIT LIDS)
Exponential Error Bounds for Random Codes on the BSC