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Tuesday, October 2, 2018Seminar 217, Risk Management: Predicting Portfolio Return Volatility at Median HorizonsSeminar: Risk Seminar  October 2  11 a.m.12:30 p.m.  1011 Evans Hall Speaker: Dangxing Chen, UC Berkeley Consortium for Data Analytics in Risk Commercially available factor models provide good predictions of shorthorizon (e.g. one day or one week) portfolio volatility, based on estimated portfolio factor loadings and responsive estimates of factor volatility. These predictions are of significant value to certain shortterm investors, such as hedge funds. However, they provide limited guidance to longterm investors, such as Defined... More > The challenge of big data and data science for the social sciences: Berkeley Distinguished Lectures in Data ScienceLecture: Other Related Seminars  October 2  4:105 p.m.  190 Doe Library Henry Brady, Dean, Goldman School of Public Policy; Henry Brady, Dean, Goldman School of Public Policy Berkeley Institute for Data Science The 2005 National Science Foundation workshop report on "Cyberinfrastructure for the Social and Behavioral Sciences" (Fran Berman and Henry Brady) argued that the methods of doing research in the social sciences would be transformed by big data and data science and that the social sciences should be centrally involved in studying the impacts of big data and data science on society. In "The... More > All Audiences All Audiences Wednesday, October 3, 2018Concentration from Geometry in High DimensionSeminar: Probability Seminar  October 3  34 p.m.  1011 Evans Hall Santosh Vempala, Georgia Tech The concentration of Lipschitz functions around their expectation is a classical topic that continues to be very active. We will discuss some recent progress, including: Statistical challenges in casualty estimationSeminar: Neyman Seminar  October 3  45 p.m.  1011 Evans Hall Kristian Lum, Human Rights Data Analysis Group An accurate understanding of the magnitude and dynamics of casualties during a conflict is important for a variety of reasons, including historical memory, retrospective policy analysis, and assigning culpability for human rights violations. However, during times of conflict and their aftermath, collecting a complete or representative sample of casualties can be difficult if not impossible. One... More > Center for Computational Biology Seminar: Dr. Quaid Morris, Professor, Donnelly Centre for Cellular and Biomolecular Research, University of TorontoSeminar: Other Related Seminars  October 3  4:305:30 p.m.  101 Life Sciences Addition Center for Computational Biology Title: Making sense of the “noise” in cancer data Tuesday, October 9, 2018Seminar 217, Risk Management: Robust Learning: Information Theory and AlgorithmsSeminar: Risk Seminar  October 9  11 a.m.12:30 p.m.  1011 Evans Hall Speaker: Jacob Steinhardt, Stanford Consortium for Data Analytics in Risk This talk will provide an overview of recent results in highdimensional robust estimation. The key question is the following: given a dataset, some fraction of which consists of arbitrary outliers, what can be learned about the nonoutlying points? This is a classical question going back at least to Tukey (1960). However, this question has recently received renewed interest for a combination of... More > Letters of recommendation in Berkeley undergraduate admissions: Program evaluation and natural language processing: Berkeley Distinguished Lectures in Data ScienceLecture: Other Related Seminars  October 9  4:105 p.m.  190 Doe Library Jesse Rothstein, Professor, Public Policy and Economics, UC Berkeley Berkeley Institute for Data Science In Fall 2015 and 2016, UC Berkeley asked many freshman applicants to submit letters of recommendation as part of their applications. This was highly controversial. Proponents argued that letters would aid in the identification of disadvantaged students who had overcome obstacles that were not otherwise apparent from their applications, while opponents argued that disadvantaged students were... More > All Audiences All Audiences Wednesday, October 10, 2018Large deviations of subgraph counts for sparse Erd\H{o}sR\'enyi graphsSeminar: Probability Seminar  October 10  34 p.m.  1011 Evans Hall Nicholas Cook, UCLA For each fixed integer $\ell\ge 3$ we establish the leading order of the exponential rate function for the probability that the number of cycles of length $\ell$ in the Erd\H{o}sR\'enyi graph $G(N,p)$ exceeds its expectation by a constant factor, assuming $N^{1/2}\ll p\ll 1$ (up to log corrections) when $\ell\ge 4$, and $N^{1/3}\ll p\ll 1$ in the case of triangles. We additionally obtain the... More > To persist or not to persist?Seminar: Neyman Seminar  October 10  45 p.m.  1011 Evans Hall Sebastian Schreiber, UC Davis Two long standing, fundamental questions in biology are "Under what conditions do populations persist or go extinct? When do interacting species coexist?" The answers to these questions are essential for guiding conservation efforts and identifying mechanisms that maintain biodiversity. Mathematical models play an important role in identifying these mechanisms and, when coupled with empirical... More > Tuesday, October 16, 2018Seminar 217, Risk Management: Asymptotic Spectral Analysis of Markov Chains with Rare Transitions: A GraphAlgorithmic ApproachSeminar: Risk Seminar  October 16  11 a.m.12:30 p.m.  1011 Evans Hall Speaker: Tingyue Gan, UC Berkeley Consortium for Data Analytics in Risk Parameterdependent Markov chains with exponentially small transition rates arise in modeling complex systems in physics, chemistry, and biology. Such processes often manifest metastability, and the spectral properties of the generators largely govern their longterm dynamics. In this work, we propose a constructive graphalgorithmic approach to computing the asymptotic estimates of eigenvalues... More > Wednesday, October 17, 2018The Lovász theta function for random regular graphsSeminar: Probability Seminar  October 17  34 p.m.  1011 Evans Hall Jess Banks, UC Berkeley The Lovász theta function is a classic semidefinite relaxation of graph coloring. In this talk I'll discuss the power of this relaxation for refuting colorability of uniformly random degreeregular graphs, as well as for distinguishing this distribution from one with a `planted' disassoratative community structure. We will see that the behavior of this refutation scheme is consistent with the... More > Learning in Google Ads, Machines and PeopleSeminar: Neyman Seminar  October 17  45 p.m.  1011 Evans Hall Niall Cardin, Google This talk is in two parts, both of which discuss interesting uses of experiments in Google search ads. In part 1 I discuss how we can inject randomness into our system to get causal inference in a machine learning setting. In part 2. I talk about experiment designs to measure how users learn in response to ads on Google.com. Friday, October 19, 20184th Annual CDAR Symposium 2018Conference/Symposium: Risk Seminar  October 19  8:30 a.m.6:30 p.m.  Memorial Stadium, University Club Consortium for Data Analytics in Risk Our conference will feature new developments in data science, highlighting applications to finance and risk management. Confirmed speakers include Jeff Bohn, Olivier Ledoit, Ulrike Malmendier, Steven Kou, Ezra Nahum, Roy Henriksson, and Ken Kroner. All Audiences All Audiences RSVP by October 12 online, or or by emailing Sang Oum at soum@berkeley.edu. Tuesday, October 23, 2018Seminar 217, Risk Management: Proliferation of Anomalies and Zoo of Factors – What does the Hansen–Jagannathan Distance Tell Us?Seminar: Risk Seminar  October 23  11 a.m.12:30 p.m.  1011 Evans Hall Speaker: Xiang Zhang, SWUFE Consortium for Data Analytics in Risk Recent research finds that prominent asset pricing models have mixed success in evaluating the crosssection of anomalies, which highlights proliferation of anomalies and zoo of factors. In this paper, I investigate that how is the relative pricing performance of these models to explain anomalies, when comparing their misspecification errors– the Hansen–Jagannathan (HJ) distance measure. I find... More > Optimal robot action for and around people: Berkeley Distinguished Lectures in Data ScienceLecture: Other Related Seminars  October 23  4:105 p.m.  190 Doe Library Anca Dragan, Professor, Electrical Engineering and Computer Sciences, UC Berkeley Berkeley Institute for Data Science Estimation, planning, control, and learning are giving us robots that can generate good behavior given a specified objective and set of constraints. What I care about is how humans enter this behavior generation picture, and study two complementary challenges: 1) how to optimize behavior when the robot is not acting in isolation, but needs to coordinate or collaborate with people; and 2) what to... More > All Audiences All Audiences Wednesday, October 24, 2018Constructing (2+1)dimensional KPZ evolutionsSeminar: Probability Seminar  October 24  34 p.m.  1011 Evans Hall Alex Dunlap, Stanford University The (d+1)dimensional KPZ equation Safe Learning in RoboticsSeminar: Neyman Seminar  October 24  45 p.m.  1011 Evans Hall Claire Tomlin, UC Berkeley A great deal of research in recent years has focused on robot learning. In many applications, guarantees that specifications are satisfied throughout the learning process are paramount. For the safety specification, we present a controller synthesis technique based on the computation of reachable sets, using optimal control and game theory. In the first part of the talk, we will review these... More > Wednesday, October 31, 2018Rigidity and tolerance for perturbed latticesSeminar: Probability Seminar  October 31  34 p.m.  1011 Evans Hall Yuval Peres, Microsoft Research Consider a perturbed lattice {v+Y_v} obtained by adding IID ddimensional Gaussian variables {Y_v} to the lattice points in Z^d. 

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