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Wednesday, February 14, 2018Eric Friedlander  MeanField Methods In Large Stochastic NetworksSeminar  February 14  3:305 p.m.  540 Cory Hall Eric Friedlander, University of North Carolina  Chapel Hill Industrial Engineering & Operations Research Abstract: Analysis of largescale communication networks (e.g. ad hoc wireless networks, cloud computing systems, server networks etc.) is of great practical interest. The massive size of such networks frequently makes direct analysis intractable. Asymptotic approximations using hydrodynamic and diffusion scaling limits provide useful methods for approaching such problems. In this talk, we study... More > Friday, February 16, 2018Zeyu Zheng  TopDown Statistical ModelingSeminar  February 16  23:30 p.m.  3108 Etcheverry Hall Zeyu Zheng, Stanford University Industrial Engineering & Operations Research Abstract: In this talk, we will argue that datadriven service systems engineering should take a statistical perspective that is guided by the decisions and performance measures that are critical from a managerial perspective. We further take the view that the statistical models will often be used as inputs to simulations that will be used to drive either capacity decisions or realtime decisions... More > Wednesday, February 21, 2018Weina Wang Delay Bounds And Asymptotics In Cloud Computing SystemsSeminar: Distinguished Lecture Series  February 21  3:305 p.m.  3110 Etcheverry Hall Weina Wang, Illinois UrbanaCampaign Industrial Engineering & Operations Research With the emergence of bigdata technologies, cloud computing systems are growing rapidly in size and becoming more and more complex, making it costly to conduct experiments and simulations. Therefore, modeling computing systems and characterizing their performance analytically are more critical than ever in identifying bottlenecks, informing system design, and facilitating provisioning. Monday, February 26, 2018Barna Saha  Efficient FineGrained AlgorithmsSeminar  February 26  3:305 p.m.  3108 Etcheverry Hall Barna Saha, University of Massachusetts Amherst Industrial Engineering & Operations Research Abstract: One of the greatest successes of computational complexity theory is the classification of countless fundamental computational problems into polynomialtime and NPhard ones, two classes that are often referred to as tractable and intractable, respectively. However, this crude distinction of algorithmic efficiency is clearly insufficient when handling today's large scale of data. We need... More > Monday, April 2, 2018Agostino Capponi  Columbia UniversitySeminar: Distinguished Lecture Series  April 2  3:305 p.m.  3108 Etcheverry Hall Agostino Capponi, Columbia University Industrial Engineering & Operations Research Agostino Capponi joined Columbia University's IEOR Department in August 2014, where he is also a member of the Institute for Data Science and Engineering. Thursday, April 5, 2018Robots on the Edge: Intelligent Machines, Industry 4.0 and Fog RoboticsPanel Discussion  April 5  11:30 a.m.1:30 p.m.  UC Santa Cruz, Silicon Valley Campus 3175 Bowers Avenue, Santa Clara, CA 95054 Ken Goldberg, Professor of Industrial Engineering and Operations Research, UC Berkeley, CITRIS and the Banatao Institute; Juan Aparicio, Head of Research Group Advanced Manufacturing Automation, Siemens Corporation CITRIS and the Banatao Institute Please join us for the CITRIS Silicon Valley Forum, a new monthly series from CITRIS and the Banatao Institute. Our second panel of the Spring 2018 series invites Ken Goldberg, Professor of Industrial Engineering and Operations Research and Juan Aparicio, Head of Research Group Advanced Manufacturing Automation at Siemens to discuss Robots on the Edge: Intelligent Machines, Industry 4.0, and Fog... More > All Audiences, Faculty, Friends of the University, General Public, Students  Graduate All Audiences Monday, April 16, 2018Rahul Jain — Reinforcement Learning without ReinforcementSeminar  April 16  3:304:30 p.m.  3108 Etcheverry Hall Rahul Jain, University of Southern California Industrial Engineering & Operations Research Abstract: Reinforcement Learning (RL) is concerned with solving sequential decisionmaking problems in the presence of uncertainty. RL is really about two problems together. The first is the `Bellman problem’: Finding the optimal policy given the model, which may involve large state spaces. Various approximate dynamic programming and RL schemes have been developed, but either there are no... More > Monday, April 30, 2018Avraham Shtub TechnionSeminar: Distinguished Lecture Series  April 30  3:305 p.m.  3108 Etcheverry Hall Avraham Shtub, Technion Industrial Engineering & Operations Research Professor Avraham Shtub holds the Stephen and Sharon Seiden Chair in Project Management. He was a faculty member of the department of Industrial Engineering at Tel Aviv University from 1984 to 1998 where he also served as a chairman of the department (19931996)... More > Monday, May 7, 2018BLISS Seminar: Learning with Low Approximate Regret with Partial FeedbackSeminar  May 7  34 p.m.  540 Cory Hall Eva Tardos Electrical Engineering and Computer Sciences (EECS) We consider the adversarial multiarmed bandit problem with partial feedback, minimizing a nonnegative loss function using the graph based feedback framework introduced by Mannor and Shamir in 2011. We offer algorithms that attain small loss bounds, as well as low approximate regret against a shifting comparator. Friday, June 15, 2018Let's be Flexible: Soft Haptics and Soft RoboticsSeminar  June 15  12 p.m.  540AB Cory Hall Allison Okamura, Stanford University Electrical Engineering and Computer Sciences (EECS) While traditional robotic manipulators are constructed from rigid links and localized joints, a new generation of robotic devices are soft, using flexible, deformable materials. In this talk, I will describe several new systems that leverage softness to achieve novel shape control, provide a compliant interface to the human body, and access hardtoreach locations... More > Tuesday, July 31, 2018Seminar 217, Risk Management: A Term Structure Model for Dividends and Interest RatesSeminar  July 31  23:30 p.m.  1011 Evans Hall Speaker: Damir Filipović, Ecole Polytechnique Fédérale de Lausanne Consortium for Data Analytics in Risk Over the last decade, dividends have become a standalone asset class instead of a mere side product of an equity investment. We introduce a framework based on polynomial jumpdiffusions to jointly price the term structures of dividends and interest rates. Prices for dividend futures, bonds, and the dividend paying stock are given in closed form. Tuesday, August 28, 2018Seminar 217, Risk Management: Is motor insurance ratemaking going to change with telematics and semiautonomous vehicles?Seminar  August 28  11 a.m.12:30 p.m.  1011 Evans Hall Speaker: Montserrat Guillen, University of Barcelona Consortium for Data Analytics in Risk Many automobile insurance companies offer the possibility to monitor driving habits and distance driven by means of telematics devices installed in the vehicles. This provides a novel source of data that can be analysed to calculate personalised tariffs. For instance, drivers who accumulate a lot of miles should be charged more for their insurance coverage than those who make little use of their... More > Tuesday, September 4, 2018Seminar 217, Risk Management: On Optimal Options Book Execution Strategies with Market ImpactSeminar  September 4  11 a.m.12:30 p.m.  1011 Evans Hall Speaker: Saad Mouti, UC Berkeley Consortium for Data Analytics in Risk We consider the optimal execution of a book of options when market impact is a driver of the option price. We aim at minimizing the meanvariance risk criterion for a given market impact function. First, we develop a framework to justify the choice of our market impact function. Our model is inspired from Leland’s option replication with transaction costs where the market impact is directly part... More > Tuesday, September 11, 2018Seminar 217, Risk Management: Capacity constraints in earning, and asset prices before earnings announcementsSeminar  September 11  11 a.m.12:30 p.m.  1011 Evans Hall Speaker: Tamas Batyi, UC Berkeley Consortium for Data Analytics in Risk This paper proposes an asset pricing model with endogenous allocation of constrained learning capacity, that provides an explanation for abnormal returns before the scheduled release of information about firms, such as quarterly earnings announcements. In equilibrium investors endogenously focus their learning capacity and acquire information about stocks with upcoming announcements, resulting in... More > Saturday, September 15, 2018Science Lecture  Artificial Intelligence and the longterm future of humanityLecture  September 15  11 a.m.12:30 p.m.  100 Genetics & Plant Biology Building Stuart Russell, Department of Electrical Engineering and Computer Sciences The news media in recent years have been full of dire warnings about the risk that AI poses to the human race, coming from wellknown figures such as Stephen Hawking and Elon Musk. Should we be concerned? If so, what can we do about it? While some in the mainstream AI community dismiss these concerns, Professor Russell will argue instead that a fundamental reorientation of the field is required... More > All Audiences, Alumni, Faculty, Friends of the University, General Public, Staff, Students  Graduate, Students  Prospective, Students  Undergraduate, Cal Parents All Audiences, Alumni, Faculty, Friends of the University, General Public, Staff, Students  Graduate, Students  Prospective, Students  Undergraduate, Cal Parents Tuesday, September 18, 2018Seminar 217, Risk Management: Nonstandard Analysis and its Application to Markov ProcessesSeminar  September 18  11 a.m.12:30 p.m.  1011 Evans Hall Speaker: Haosui Duanmu, UC Berkeley Consortium for Data Analytics in Risk Nonstandard analysis, a powerful machinery derived from mathematical logic, has had many applications in probability theory as well as stochastic processes. Nonstandard analysis allows construction of a single object  a hyperfinite probability space  which satisfies all the first order logical properties of a finite probability space, but which can be simultaneously viewed as a... More > Tuesday, September 25, 2018Seminar 217, Risk Management: A Deep Learning Investigation of OneMonth MomentumSeminar  September 25  11 a.m.12:30 p.m.  1011 Evans Hall Speaker: Ben Gum, AXA Rosenberg Consortium for Data Analytics in Risk The onemonth return reversal in equity prices was first documented by Jedadeesh (1990), who found that there was a highly significant negative serial correlation in the monthly return series of stocks. This is in contrast to the positive serial correlation of the annual stock returns. Explanations for this effect differ, but the general consensus has been that the trailing onemonth return... More > Tuesday, October 2, 2018Seminar 217, Risk Management: Predicting Portfolio Return Volatility at Median HorizonsSeminar  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 > Tuesday, October 9, 2018Seminar 217, Risk Management: Robust Learning: Information Theory and AlgorithmsSeminar  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 > Tuesday, October 16, 2018Seminar 217, Risk Management: Asymptotic Spectral Analysis of Markov Chains with Rare Transitions: A GraphAlgorithmic ApproachSeminar  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 > Tuesday, October 23, 2018Seminar 217, Risk Management: Proliferation of Anomalies and Zoo of Factors – What does the Hansen–Jagannathan Distance Tell Us?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 > Tuesday, November 13, 2018Seminar 217, Risk Management: Topic ForthcomingSeminar  November 13  11 a.m.12:30 p.m.  1011 Evans Hall Speaker: Wachi Bandara, Pluribus Labs Tuesday, November 27, 2018Seminar 217, Risk Management: Topic ForthcomingSeminar  November 27  11 a.m.12:30 p.m.  1011 Evans Hall Speaker: Michael Ohlrogge, Stanford 

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