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<< September 2017 >>

Tuesday, September 5, 2017

Seminar 217, Risk Management: Sparse Low Rank Dictionary Learning

Seminar: Risk Seminar | September 5 | 11 a.m.-1 p.m. | 639 Evans Hall

Speaker: Robert Anderson, UC Berkeley

Center for Risk Management Research

Sparse Dictionary Learning (SDL) can be used to extract narrow factors driving stock returns from a stock returns matrix, provided the returns are generated by sparse factors alone.  We describe progress on a variant called Sparse Low Rank Dictionary Learning (SLRDL), designed to simultaneously extract broad and narrow factors for the returns matrix, when the returns are generated by both types...   More >

Wednesday, September 6, 2017

Sharp threshold for K4-percolation

Seminar: Probability Seminar | September 6 | 3:10-4 p.m. | 1011 Evans Hall

Brett Kolesnik, UC Berkeley

Department of Statistics

Graph bootstrap percolation is a cellular automaton introduced by Bollobas. Let H be a graph. Edges are added to an initial graph G=(V,E) if they are in a copy of H minus an edge, until no further edges can be added. If eventually the complete graph on V is obtained, G is said to H-percolate. We identify the sharp threshold for K4-percolation on the Erdos-Renyi graph G(n,p)...   More >

Stochastic First-Order Methods in Data Analysis and Reinforcement Learning

Seminar: Neyman Seminar | September 6 | 4-5 p.m. | 1011 Evans Hall

Mengdi Wang, Princeton University

Department of Statistics

Stochastic first-order methods provide a basic algorithmic tool for online learning and data analysis. In this talk, we survey several innovative applications including risk-averse optimization, online principal component analysis, dynamic network partition, Markov decision problems and reinforcement learning. We will show that convergence analysis of the stochastic optimization algorithms...   More >

Thursday, September 7, 2017

LaTeX: Creating Tables, Figures, and Bibliographies

Workshop: Other Related Seminars | September 7 | 4-5 p.m. | Bechtel Engineering Center, Kresge Engineering Library Training Room 110MD

Samantha Teplitzky, Earth and Physical Sciences Librarian, Kresge Engineering Library


This workshop will focus on how to add elements to a LaTeX document. Attendees will learn about various packages and syntax that enables the creation of tables, figures, and bibliographies.

Registration opens August 4. Register online, or by calling Samantha Teplitzky at 510-644-7158, or by emailing Samantha Teplitzky at

Monday, September 11, 2017

Yong Zeng — NSF Funding Opportunities Related to Data Science

Seminar: News and Events | September 11 | 3:30-5 p.m. | 3108 Etcheverry Hall

Yong Zeng, National Science Foundation

Industrial Engineering & Operations Research

This presentation will provide an overview of the funding opportunities related to data science in National Science Foundation. The funding opportunities will include those in the directorates of Computer & Information Science & Engineering (CISE), Engineering (ENG), and Mathematical and Physical Sciences (MPS), and the focus will be those supported by Division of Mathematical Sciences (DMS) in MPS.

Tuesday, September 12, 2017

Seminar 217, Risk Management: Social Finance and the Postmodern Portfolio: Theory and Practice

Seminar: Risk Seminar | September 12 | 11 a.m.-1 p.m. | 639 Evans Hall

Speaker: Jeremy Evnine, Evnine & Associates

Center for Risk Management Research

We formulate the portfolio construction problem as a mean/variance problem which includes a linear term representing an investor’s preference for expected “social return”, in addition to her expected “financial return” of the classical theory. By making various assumptions, we are able to exploit the heterogeneous expectations version of the CAPM to derive an equilibrium model which is an...   More >

Wednesday, September 13, 2017

Matrix Concentration for Expander Walks

Seminar: Probability Seminar | September 13 | 3:10-4 p.m. | 1011 Evans Hall

Nikhil Srivastava, UC Berkeley

Department of Statistics

We prove a Chernoff-type bound for sums of matrix-valued random variables sampled via a random walk on a Markov chain with spectral gap, confirming a conjecture of Wigderson and Xiao up to logarithmic factors in the deviation parameter. Our proof is based on a recent multi-matrix extension of the Golden-Thompson inequality due to Sutter et al. discovered in the context of quantum information...   More >

Phase transitions in random constraint satisfaction problems

Seminar: Neyman Seminar | September 13 | 4-5 p.m. | 1011 Evans Hall

Nike Sun, University of California, Berkeley

Department of Statistics

We will discuss a class of random constraint satisfaction problems (CSPs), including the boolean k-satisfiability (k-SAT) problem. For numerous random CSP models, heuristic methods from statistical physics yield detailed predictions on phase transitions and other phenomena. We will survey some of these predictions and describe some progress in the development of mathematical theory for these...   More >

Tuesday, September 19, 2017

Seminar 217, Risk Management: Change-point detection for stochastic processes

Seminar: Risk Seminar | September 19 | 11 a.m.-1 p.m. | 639 Evans Hall

Speaker: Sveinn Olafsson, Visiting Assistant Professor, UC Santa Barbara

Center for Risk Management Research

Since the work of Page in the 1950s, the problem of detecting an abrupt change in the distribution of stochastic processes has received a great deal of attention. There are two main formulations of such problems: A Bayesian approach where the change-point is assumed to be random, and a min-max approach under which the change-point is assumed to be fixed but unknown. In both cases, a deep...   More >

Wednesday, September 20, 2017


Seminar: Probability Seminar | September 20 | 3:10-4 p.m. | 1011 Evans Hall

Matthew Junge, Duke University

Department of Statistics

Parking functions were introduced by combinatorialists in the 1960s, and have recently been studied by probabilists. When the parking lot is an infinite graph and cars drive around at random, we will look at how many parking spots are needed for every car to eventually find a spot. Joint work with Michael Damron, Janko Gravner, Hanbeck Lyu, and David Sivakoff.

Adaptation via convex optimization in two nonparametric estimation problems

Seminar: Neyman Seminar | September 20 | 4-5 p.m. | 1011 Evans Hall

Adityanand Guntuboyina, University of California, Berkeley

Department of Statistics

We study two convex optimization based procedures for nonparametric function estimation: trend filtering (or higher order total variation denoising) and the Kiefer-Wolfowitz MLE for Gaussian location mixtures. Trend filtering can be seen as a technique for fitting spline-like functions for nonparametric regression with adaptive knot selection. It can also be seen as a special case of LASSO for a...   More >

Friday, September 22, 2017

Jacobs Design Conversations: Eric Rodenbeck, "Telling Stories with Data"

Lecture: Other Related Seminars | September 22 | 12-1 p.m. | 310 Jacobs Hall

Jacobs Institute for Design Innovation

Stamen founder, CEO, and creative director Eric Rodenbeck will speak at Jacobs Hall as part of the Jacobs Design Conversations series.

All Audiences

All Audiences

Monday, September 25, 2017

Adam Elmachtoub - The value of opaque products

Seminar: Other Related Seminars | September 25 | 3:30-5 p.m. | 3108 Etcheverry Hall

Adam Elmachtoub, Columbia University

Industrial Engineering & Operations Research

Abstract: A product is said to be opaque if one or more of its attributes are not revealed until after the product has been sold. Opaque products have historically been used in the travel industry where airline and hotel brands might be hidden to the customer, in exchange for a discount. More recently, online retailers have also used opaque products, where customers can sacrifice their choice of...   More >

Tuesday, September 26, 2017

Seminar 217, Risk Management: Machine Learning and Alternative Data in Fundamental-based Quantitative Equity

Seminar: Risk Seminar | September 26 | 11 a.m.-1 p.m. | 639 Evans Hall

Speaker: Ben Gum, AXA Rosenberg

Center for Risk Management Research

We begin with a survey of machine learning techniques and applications outside of finance. Then we discuss our use of Machine Learning techniques at Rosenberg. Finally, we explore some alternative data sources.

Life 3.0: Being Human in the Age of Artificial Intelligence: A talk by Max Tegmark

Lecture: Other Related Seminars | September 26 | 3:30-4:30 p.m. | Soda Hall, 430-8 Wozniak Lounge

Max Tegmark, Massachusetts Institute of Technology

Electrical Engineering and Computer Sciences (EECS)

How can we grow our prosperity through automation without leaving people lacking income or purpose? What career advice should we give today’s kids? How can we make future AI systems more robust, so that they do what we want without crashing, malfunctioning or getting hacked? Should we fear an arms race in lethal autonomous weapons? Will machines eventually outsmart us at all tasks, replacing...   More >

Staff, Students - Graduate, Students - Undergraduate

All Audiences

Berkeley Distinguished Lectures in Data Science: On Computational Thinking, Inferential Thinking and Data Science

Seminar | September 26 | 4:10-5 p.m. | 190 Doe Library

Michael I. Jordan, Professor, Statistics & EECS, UC Berkeley

Berkeley Institute for Data Science

The rapid growth in the size and scope of datasets in science and technology has created a need for novel foundational perspectives on data analysis that blend the inferential and computational sciences. That classical perspectives from these fields are not adequate to address emerging problems in Data Science is apparent from their sharply divergent nature at an elementary level---in computer...   More >

Wednesday, September 27, 2017

Invertibility and condition number of sparse random matrices

Seminar: Probability Seminar | September 27 | 3:10-4 p.m. | 1011 Evans Hall

Mark Rudelson, University of Michigan

Department of Statistics

Consider an n by n linear system Ax=b. If the right-hand side of the system is known up to a certain error, then in process of the solution, this error gets amplified by the condition number of the matrix A, i.e. by the ratio of its largest and smallest singular values. This observation led von Neumann and his collaborators to consider the condition number of a random matrix and conjecture that...   More >

Negative Dependence and Sampling in Machine Learning

Seminar: Neyman Seminar | September 27 | 4-5 p.m. | 1011 Evans Hall

Stefanie Jegelka, Massachusetts Institute of Technology

Department of Statistics

Discrete Probability distributions with strong negative dependencies (negative association) occur in a wide range of settings in Machine Learning, from probabilistic modeling to randomized algorithms for accelerating a variety of popular ML models. In addition, these distributions enjoy rich theoretical connections and properties. A prominent example are Determinantal Point Processes.
In this...   More >

Thursday, September 28, 2017

GraphXD Seminar: Graph Clustering Algorithms

Seminar | September 28 | 5:30-7 p.m. | 1011 Evans Hall

Tselil Schramm, Simons Institute, UC Berkeley

Berkeley Institute for Data Science

One of the greatest advantages of representing data with graphs is access to generic algorithms for analytic tasks, such as clustering. In this talk I will describe some popular graph clustering algorithms, and explain why they are well-motivated from a theoretical perspective.