Graduate

Statistics Seminar: Understanding rare events in models of statistical mechanics

Topic: 
Understanding rare events in models of statistical mechanics
Abstract / Description: 

Statistical mechanics models are ubiquitous at the interface of probability theory, information theory, and inference problems in high dimensions. To develop a refined understanding of such models, one often needs to study not only typical fluctuation theory but also the realm of atypical events. In this talk, we will focus on sparse networks and polymer models on lattices. In particular we will consider the rare events that a sparse random network has an atypical number of certain local structures, and that a polymer in random media has atypical weight. The random geometry associated with typical instances of these rare events is an important topic of inquiry: this geometry can involve merely local structures, or more global ones. We will discuss recent solutions to certain longstanding questions and connections to stochastic block models, exponential random graphs, eigenvalues of random matrices, and fundamental growth models.

Date and Time: 
Tuesday, January 30, 2018 - 4:30pm
Venue: 
Sloan Mathematics Building, Room 380Y

Networking Seminar presents Wenting Zheng

Topic: 
Clipper: A Low-Latency, General-Purpose Prediction Serving System
Abstract / Description: 

Stanford's NetSeminar is a biweekly seminar covering networking-related topics. Speakers come from academia and industry and the talks are open to the public. When possible, talks will be recorded and posted online. We typically start at 12:15pm at Gates Bld — Room 104, unless otherwise mentioned.

NetSeminar is run by graduate students, and it is generously supported by the Stanford Computer Forum.

Date and Time: 
Thursday, April 5, 2018 - 12:15pm
Venue: 
Gates 104

Networking Seminar presents Arjun Singhvi

Topic: 
TBA
Abstract / Description: 

Stanford's NetSeminar is a biweekly seminar covering networking-related topics. Speakers come from academia and industry and the talks are open to the public. When possible, talks will be recorded and posted online. We typically start at 12:15pm at Gates Bld — Room 104, unless otherwise mentioned.

NetSeminar is run by graduate students, and it is generously supported by the Stanford Computer Forum.

Date and Time: 
Thursday, March 15, 2018 - 12:15pm
Venue: 
Gates 104

Networking Seminar presents Israel Cidon

Topic: 
TBA
Abstract / Description: 

Stanford's NetSeminar is a biweekly seminar covering networking-related topics. Speakers come from academia and industry and the talks are open to the public. When possible, talks will be recorded and posted online. We typically start at 12:15pm at Gates Bld — Room 104, unless otherwise mentioned.

NetSeminar is run by graduate students, and it is generously supported by the Stanford Computer Forum.

Date and Time: 
Friday, March 2, 2018 - 3:30pm
Venue: 
Gates 415

Networking Seminar presents Aurojit Panda

Topic: 
TBA
Abstract / Description: 

Stanford's NetSeminar is a biweekly seminar covering networking-related topics. Speakers come from academia and industry and the talks are open to the public. When possible, talks will be recorded and posted online. We typically start at 12:15pm at Gates Bld — Room 104, unless otherwise mentioned.

NetSeminar is run by graduate students, and it is generously supported by the Stanford Computer Forum.

Date and Time: 
Thursday, February 15, 2018 - 12:15pm
Venue: 
Gates 104

Networking Seminar: Clipper: A Low-Latency, General-Purpose Prediction Serving System

Topic: 
Clipper: A Low-Latency, General-Purpose Prediction Serving System
Abstract / Description: 

Machine learning is being deployed in a growing number of applications which demand real-time, accurate, and robust predictions under heavy serving loads. However, most machine learning frameworks and systems only address model training and not deployment.

Clipper is an open-source, general-purpose model-serving system that addresses these challenges. Interposing between applications that consume predictions and the machine-learning models that produce predictions, Clipper simplifies the model deployment process by adopting a modular serving architecture and isolating models in their own containers, allowing them to be evaluated using the same runtime environment as that used during training. Clipper's modular architecture provides simple mechanisms for scaling out models to meet increased throughput demands and performing fine-grained physical resource allocation for each model. Further, by abstracting models behind a uniform serving interface, Clipper allows developers to compose many machine-learning models within a single application to support increasingly common techniques such as ensemble methods, multi-armed bandit algorithms, and prediction cascades. In this talk I will provide an overview of the Clipper serving system and then discuss some of our work developing Clipper into an active open-source project.


 

Stanford's NetSeminar is a biweekly seminar covering networking-related topics. Speakers come from academia and industry and the talks are open to the public. When possible, talks will be recorded and posted online. We typically start at 12:15pm at Gates Bld — Room 104, unless otherwise mentioned.

NetSeminar is run by graduate students, and it is generously supported by the Stanford Computer Forum.

Date and Time: 
Thursday, February 1, 2018 - 3:00pm
Venue: 
Gates 104

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