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Conference

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Navigating Optics Coursework at Stanford

Topic: 
Navigating Optics Coursework at Stanford
Abstract / Description: 

The panelists are optics PhD students and postdocs from various departments who will be discussing the influence of Stanford courses on their educational and research interests.

This event is mostly geared toward 1st and 2nd year graduate students interested in optics research. We are attempting to cover courses APPPHYS 203, 304, 387, PHYSICS 321, EE 134, 136, 223, 234, 236A-C, 331, 332, 336, 340, 346, MATSCI 199.

If you are planning on joining us, please RSVP at the link below, to give us an idea how many refreshments to prepare
https://docs.google.com/forms/d/1xyDQ9AS7a9LZJ7fBMz5MC-_kDTnvftC9_QPuxTBOBWM/viewform.

Sponsored by Stanford Optical Society and Stanford Photonics Research Center

Date and Time: 
Wednesday, November 19, 2014 - 2:50pm to Thursday, November 20, 2014 - 3:55pm
Venue: 
Spilker 317

SmartGrid: Trust-Tech: A Novel Paradigm for Nonlinear Optimization and Practical Applications

Topic: 
Trust-Tech: A Novel Paradigm for Nonlinear Optimization and Practical Applications
Abstract / Description: 

Optimization technology has practical applications in almost every branch of science, business and technology. Indeed, a large variety of the quantitative issues such as decision-making, design, operation, planning, and scheduling arising in science, engineering, and economics can be perceived and modeled as nonlinear optimization problems. The solution space (i.e. search space) of nonlinear optimization problems generally contains only one global optimal solution and many local optimal solutions. The values of an objective function at local optimal solutions and at the global optimal solution may differ significantly. Hence, from a practical viewpoint, there are strong motivations to develop effective methods for finding the global optimal solution. In this talk, I will present a novel paradigm, termed Trust-Tech, for nonlinear optimization. The theoretical basis for and practical applications of Trust-Tech to Optimal Power Flow of two major utilities will also be presented.

Date and Time: 
Monday, November 17, 2014 - 1:00pm to Tuesday, November 18, 2014 - 1:55pm
Venue: 
Y2E2 101
Tags: 

Laser Khet Tournament (pls note time change)

Topic: 
Laser Khet Tournament
Abstract / Description: 

Ever wanted to defeat your most fearsome opponents with laser beams? Well, now you can! Join us for the first annual Laser Khet tournament in Packard atrium. For those who haven't played it before, Laser Khet is a variant of chess that includes beam splitters, mirrors, and lasers!

Drinks and snacks will be provided, and the winner of the tournament will walk home with his or her very own Laser Khet board game (batteries included)!

Even if you aren't interested in playing, feel free to drop by and cheer on your comrades!

This will be a single elimination tournament with two games running simultaneously. Each turn will be limited to 30 seconds. If you would like to have some practice before the games, feel free to come half an hour early, and we can go over the rules or play a quick friendly match.

For those that would like to enter, please sign up through the following link before Thursday at 11:59pm:
https://docs.google.com/forms/d/1P3Hf5hSPOpIZ1dJVtq7RDAk9vmr3BG4PSFOndzOpZaM/viewform

Date and Time: 
Friday, November 21, 2014 - 5:30pm to Saturday, November 22, 2014 - 6:55pm
Venue: 
Packard Atrium
Tags: 

ATLAS experiment at the Large Hadron Collider

Topic: 
ATLAS experiment at the Large Hadron Collider
Abstract / Description: 

SPRC Women in Science Seminar

The Large Hadron Collider, an accelerator in Switzerland which collides protons at the highest person-made energies in history, is trying to uncover the fundamental structure of matter and our universe. To do so, it produces roughly 100 terabytes of data per second. The experiments can only record 1 gigabyte per second. In this talk, I'll describe how we use fast algorithms in custom electronics to decide which of the 0.001% of collisions to keep and how we know that we aren't throwing away valuable Higgs bosons, dark matter particles or other messengers of new physics.


Lunch will be provided for registered attendees

RSVP here

Date and Time: 
Tuesday, November 18, 2014 - 12:00pm to Wednesday, November 19, 2014 - 12:55pm
Venue: 
Spilker 143
Tags: 

GSEE Afternoon Tea

Topic: 
EE Community
Abstract / Description: 

Take a break this Wednesday afternoon to enjoy some beverages, snacks, and conversation!

All members of the EE community - students, faculty, and staff - are welcome.

Don't forget to bring a reusable mug if you have one.

Hope to see you there!

Date and Time: 
Wednesday, November 12, 2014 - 3:00pm to Thursday, November 13, 2014 - 3:55pm
Venue: 
Packard, 2nd floor kitchen
Tags: 

EE Undergraduate Event

Topic: 
EE Undergraduate Event
Abstract / Description: 

Undergraduate Event

Please join us to hear presentations from undergraduates and discover if EE is right for you.

  • Presentations will be from 4:15pm-5:05pm in Packard 101 and the networking event will be held in the Packard Atrium from 5:05pm-6:00pm
  • Any undergraduate student is invited to attend the presentation about EE as an undergraduate major. There will be several student speakers and a Q&A session.
  • Dinner will be served from Cafe Taxim.
Date and Time: 
Monday, November 10, 2014 - 4:15pm to Tuesday, November 11, 2014 - 5:55pm
Venue: 
Packard 101

Statistics Seminar: Optimal Inference After Model Selection

Topic: 
Optimal Inference After Model Selection
Abstract / Description: 

To perform inference after model selection, we propose controlling the selective type I error; i.e., the error rate of a test given that it was performed. By doing so, we recover long-run frequency properties among selected hypotheses analogous to those that apply in the classical (non-adaptive) context. Our proposal is closely related to data splitting and has a similar intuitive justification, but is more powerful. Exploiting the classical theory of Lehmann and Scheffe (1955), we derive most powerful unbiased selective tests and confidence intervals for inference in exponential family models after arbitrary selection procedures. For linear regression, we derive new selective z-tests that generalize recent proposals for inference after model selection and improve on their power, and new selective t-tests that do not require knowledge of the error variance σ2.


This is based on joint work with Dennis Sun and Jonathan Taylor

Date and Time: 
Tuesday, December 2, 2014 - 4:15pm to 5:15pm
Venue: 
Sloan Mathematics Building 380 Room 380C
Tags: 

Statistics Seminar: Regularized and contextualized spectral clustering

Topic: 
Regularized and contextualized spectral clustering
Abstract / Description: 

In network data, relationships can be observed (e.g., as in a social network) or be built by
some similarity function (e.g., between data points in euclidean space). To find clusters
in such data, spectral clustering utilizes the eigenvectors of a similarity matrix, where the
(i, j)th element measures the similarity between points i and j. Unfortunately, the standard
spectral clustering algorithm fails when the similarity matrix is sparse (a common regime).
This talk will first discuss how a regularized spectral clustering algorithm can correct for
the problems created by this failure. The statistical improvements from regularization
are apparent in practice. The talk will theoretically characterize the improvement from
regularization under the degree corrected Stochastic Blockmodel. The talk will also discuss
contextualized spectral clustering in which the actors in the network have attributes that
correlate with the communities in the social network. We study the misclustering rate
of our proposed algorithm under a joint mixture model on the network and the node
covariates; this characterizes the algorithm as a statistical estimator. Applications with a
1,000,000 node DTI neuroconnectome and a 4,000,000 node online social network motivate
the analysis.


Cookies served at 3:45pm, 1st floor Lounge.

Date and Time: 
Tuesday, November 11, 2014 - 4:15pm to 5:15pm
Venue: 
Sloan Mathematics Building 01-380 Room 380C
Tags: 

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