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Events for June 07, 2017
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NAMRC/MSEC/ICM&P International Manufacturing Research ConferenceWed, Jun 07, 2017
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Various, NAMRC/MSEC/ICM&P International Manufacturing Research Conference
Talk Title: NAMRC/MSEC/ICM&P International Manufacturing Research Conference
Abstract: To attend:
Go to http://2017namrc-msec.usc.edu/ and register for the conference.
Host: Yong Chen
More Info: http://2017namrc-msec.usc.edu/
Audiences: Everyone Is Invited
Contact: Michele ISE
Event Link: http://2017namrc-msec.usc.edu/
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PhD Defense - Zahra Nazari
Wed, Jun 07, 2017 @ 01:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Candidate: Zahra Nazari
Date: Wed, June 7th
Time : 1 PM
Location: KAP134
Committee :
Dr. Jonathan Gratch
Dr. Milind Tambe
Dr Peter Kim
Title : Automated Negotiation with Humans
Negotiation is a crucial skill in personal and organizational interactions. In the last two decades, there has been a growing interest to create agents that can autonomously negotiating with other agents. The focus of this thesis, however, is on creating agents that can negotiate with human opponents. Besides improving on artificial social intelligence, such agents could be used for the purpose of training or assisting human negotiators. A central challenge is to handle the complexity of actual human behavior. When compared with idealized game-theoretic models,
human negotiations are far richer, both in terms of the nature of information exchanged and the number of factors that inform their decision-making.
We consider a negotiation task that is simple, yet general enough to drive agent-human research, and
analyze an extensive data set of transcribed human negotiation on such tasks.
Based on human behavior in this task, and the previous research on human negotiations, we propose a new framework to structure the design of agents that negotiate with people. We address two main decision problems inspired by this framework: modeling and influencing the opponent. Three techniques are proposed to model an opponent's preferences and character (e.g. honesty and personality traits) and a misrepresentation technique is then used to influence the opponent and gain better profit. The proposed techniques are then implemented in automatic web-based agents. We ran a number of negotiations between these agents and humans recruited on Amazon Mechanical Turk. The resulting data show that the agents can perform these strategies successfully when negotiating with human counterparts and give us valuable insight about the behavior of humans when negotiating with an agent.
Location: Kaprielian Hall (KAP) - 134
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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PhD Defense - Rose Yu
Wed, Jun 07, 2017 @ 01:30 PM - 03:30 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Candidate: Rose Yu
Date: June 7, 2017
Time: 1:30-3:30pm
Location: SAL 213
Committee:
Yan Liu
Cyrus Shahabi
Mahdi Soltanolkotabi (outside member)
Title:
Tensor learning for Large-Scale Spatiotemporal Analysis
Abstract:
Spatiotemporal data is ubiquitous in our daily life, including climate, transportation,
and social media. Today, data is being collected at an unprecedented scale.
Yesterdays concepts and tools are insufficient to serve tomorrow's data-driven
decision makers. Particularly, spatiotemporal data often demonstrates complex
dependency structures and is of high dimensionality. This requires new machine
learning algorithms that can handle highly correlated samples, perform efficient
dimension reduction, and generate structured predictions.
In this talk, I will present tensor methods, a scalable framework for capturing
high-order structures in spatiotemporal data. I will demonstrate how to learn from
spatiotemporal data efficiently in both offline and online setting. I will also show
interesting discoveries by our methods in climate and social media applications.
Location: 213
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
