- talks - lists.cs.princeton.edu

Colloquium Speaker Robert West, Friday April 15- 12:30pm
by Mitra D. Kelly 11 Apr '16

11 Apr '16

Colloquium Speaker Robert West, Infolab at Stanford University Friday April 15- 12:30pm Computer Science 105 Human Behavior in Networks Humans as well as information are organized in networks. Interacting with these networks is part of our daily lives: we talk to friends in our social network; we find information by navigating the Web; and we form opinions by listening to others and to the media. Thus, understanding, predicting, and enhancing human behavior in networks poses … [View More]important research problems for computer and data science with practical applications of high impact. In this talk I will present some of my work in this area, focusing on (1) human navigation of information networks and (2) person-to-person opinions in social networks. Network navigation constitutes a fundamental human behavior: in order to make use of the information and resources around us, we constantly explore, disentangle, and navigate networks such as the Web. Studying navigation patterns lets us understand better how humans reason about complex networks and lets us build more human-friendly information systems. As an example, I will present an algorithm for improving website hyperlink structure by mining raw web server logs. The resulting system is being deployed on Wikipedia's full server logs at terabyte scale, producing links that are clicked 10 times as frequently as the average link added by human Wikipedia editors. Communication and coordination through natural language is another prominent human network behavior. Studying the interplay of social network structure and language has the potential to benefit both sociolinguistics and natural language processing. Intriguing opportunities and challenges have arisen recently with the advent of online social media, which produce large amounts of both network and natural language data. As an example, I will discuss my work on person-to-person sentiment analysis in social networks, which combines the sociological theory of structural balance with techniques from natural language processing, resulting in a machine learning model for sentiment prediction that clearly outperforms both text-only and network-only versions. I will conclude the talk by sketching interesting future directions for computational approaches to studying and enhancing human behavior in networks. Bio: Robert West is a sixth-year Ph.D. candidate in Computer Science in the Infolab at Stanford University, advised by Jure Leskovec. His research aims to understand, predict, and enhance human behavior in social and information networks by developing techniques in data science, data mining, network analysis, machine learning, and natural language processing. Previously, he obtained a Master's degree from McGill University in 2010 and a Diplom degree from Technische Universität München in 2007. Mitra Kelly Academic Secretary Princeton University Computer Science Dept 35 Olden Street Princeton NJ 08540 mkelly(a)cs.princeton.edu <mailto:mkelly@cs.princeton.edu> 609-258-4562 [View Less]

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Colloquium Speaker: Andrej Karpathy Monday April 11, 12:30pm
by Nicole E. Wagenblast 11 Apr '16

11 Apr '16

Colloquium Speaker Andrej Karpathy, Stanford University Monday, April 11- 12:30pm Computer Science 105 Connecting Images and Natural Language Intelligent agents require the ability to perceive their environments, understand their high-level semantics, and communicate with humans. While computer vision has recently made great strides on visual recognition tasks, the predominant paradigm is to predict one or more fixed visual categories for each image. I will describe a line of work that … [View More]

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Colloquium Speaker: Andrej Karpathy Monday April 11, 12:30pm-reminder
by Nicole E. Wagenblast 10 Apr '16

10 Apr '16

Colloquium Speaker Andrej Karpathy, Stanford University Monday, April 11- 12:30pm Computer Science 105 Connecting Images and Natural Language Intelligent agents require the ability to perceive their environments, understand their high-level semantics, and communicate with humans. While computer vision has recently made great strides on visual recognition tasks, the predominant paradigm is to predict one or more fixed visual categories for each image. I will describe a line of work that … [View More]

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Colloquium Speaker Robert West, Friday April 15- 12:30pm
by Mitra D. Kelly 08 Apr '16

08 Apr '16

Colloquium Speaker Robert West, Infolab at Stanford University Friday April 15- 12:30pm Computer Science 105 Human Behavior in Networks Humans as well as information are organized in networks. Interacting with these networks is part of our daily lives: we talk to friends in our social network; we find information by navigating the Web; and we form opinions by listening to others and to the media. Thus, understanding, predicting, and enhancing human behavior in networks poses … [View More]important research problems for computer and data science with practical applications of high impact. In this talk I will present some of my work in this area, focusing on (1) human navigation of information networks and (2) person-to-person opinions in social networks. Network navigation constitutes a fundamental human behavior: in order to make use of the information and resources around us, we constantly explore, disentangle, and navigate networks such as the Web. Studying navigation patterns lets us understand better how humans reason about complex networks and lets us build more human-friendly information systems. As an example, I will present an algorithm for improving website hyperlink structure by mining raw web server logs. The resulting system is being deployed on Wikipedia's full server logs at terabyte scale, producing links that are clicked 10 times as frequently as the average link added by human Wikipedia editors. Communication and coordination through natural language is another prominent human network behavior. Studying the interplay of social network structure and language has the potential to benefit both sociolinguistics and natural language processing. Intriguing opportunities and challenges have arisen recently with the advent of online social media, which produce large amounts of both network and natural language data. As an example, I will discuss my work on person-to-person sentiment analysis in social networks, which combines the sociological theory of structural balance with techniques from natural language processing, resulting in a machine learning model for sentiment prediction that clearly outperforms both text-only and network-only versions. I will conclude the talk by sketching interesting future directions for computational approaches to studying and enhancing human behavior in networks. Bio: Robert West is a sixth-year Ph.D. candidate in Computer Science in the Infolab at Stanford University, advised by Jure Leskovec. His research aims to understand, predict, and enhance human behavior in social and information networks by developing techniques in data science, data mining, network analysis, machine learning, and natural language processing. Previously, he obtained a Master's degree from McGill University in 2010 and a Diplom degree from Technische Universität München in 2007. Mitra Kelly Academic Secretary Princeton University Computer Science Dept 35 Olden Street Princeton NJ 08540 mkelly(a)cs.princeton.edu <mailto:mkelly@cs.princeton.edu> 609-258-4562 [View Less]

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Colloquium Speaker: Olga Russakovsky, Thursday, April 14, 12:30pm
by Nicole E. Wagenblast 08 Apr '16

08 Apr '16

Colloquium Speaker Olga Russakovsky, Carnegie Mellon University Thursday, April 14- 12:30pm Computer Science 105 The human side of computer vision Intelligent agents acting in the real world need advanced vision capabilities to perceive, learn from, reason about and interact with their environment. In this talk, I will explore the role that humans play in the design and deployment of computer vision systems. Large-scale manually labeled datasets have proven instrumental for scaling up visual … [View More]

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Colloquium Speaker: Andrej Karpathy Monday April 11, 12:30pm
by Nicole E. Wagenblast 07 Apr '16

07 Apr '16

Colloquium Speaker Andrej Karpathy, Stanford University Monday, April 11- 12:30pm Computer Science 105 Connecting Images and Natural Language Intelligent agents require the ability to perceive their environments, understand their high-level semantics, and communicate with humans. While computer vision has recently made great strides on visual recognition tasks, the predominant paradigm is to predict one or more fixed visual categories for each image. I will describe a line of work that … [View More]

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Colloquium Speaker Roger Grosse, TODAY April 7th- 12:30pm
by Mitra D. Kelly 07 Apr '16

07 Apr '16

Colloquium Speaker Roger Grosse, the University of Toronto April 7th- 12:30pm Computer Science 105 Exploiting compositionality to explore a large space of model structures I will present flexible algorithms for model discovery and model fitting which apply to broad, open-ended classes of models, yet which also incorporate model-specific algorithmic insights. First, I will introduce a framework for building probabilistic models compositionally out of common modeling motifs, … [View More]

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Colloquium Speaker Yin-Tat Lee, TODAY April 5th- 12:30pm
by Mitra D. Kelly 05 Apr '16

05 Apr '16

Colloquium Speaker Yin-Tat Lee, Massachusetts Institute of Technology April 5th, 12:30pm Computer Science 105 Title: Faster algorithms for fundamental convex problems and their applications in combinatorial optimization Abstract: Convex optimization has been studied extensively and is a prominent tool in various areas such as combinatorial optimization, data analysis, operations research, and scientific computing. Each field has developed specialized tools including data structures, … [View More]

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Colloquium Speaker Yin-Tat Lee, Tuesday April 5th- 12:30pm
by Mitra D. Kelly 04 Apr '16

04 Apr '16

Colloquium Speaker Yin-Tat Lee, Massachusetts Institute of Technology April 5th, 12:30pm Computer Science 105 Title: Faster algorithms for fundamental convex problems and their applications in combinatorial optimization Abstract: Convex optimization has been studied extensively and is a prominent tool in various areas such as combinatorial optimization, data analysis, operations research, and scientific computing. Each field has developed specialized tools including data structures, … [View More]

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Colloquium Speaker Philipp Kräehenbüehl, today, 12:30pm
by Nicole E. Wagenblast 04 Apr '16

04 Apr '16

Colloquium Speaker Philipp Kräehenbüehl, University of California, Berkeley Monday, April 4, 2016 - 12:30pm Computer Science 105 The many ways to understand the pixels The field of computer vision is arguably seeing one of its most transformative changes in recent history. Convolutional neural networks (CNNs) have revolutionized the field, reaching super-human performance on some long-standing computer vision tasks, such as image classification. The success of these networks is fueled … [View More]

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