EE Student Information

Graduate

EE Degree Progress Officer - open office hours

Topic: 
Degree Progress Office Hours
Abstract / Description: 

This is a reminder that I am holding office hours on Monday and Wednesday during the first 2 weeks of class.

If you have any questions or have difficulties in course registration, please feel free to meet me virtually via the Zoom link below - password required.

Date and Time: 
Wednesday, September 29, 2021 - 11:00am to 12:00pm

OSA/SPIE and GSEE Welcome Mixer

Topic: 
OSA/SPIE and GSEE Welcome Mixer
Abstract / Description: 

Along with GSEE (Stanford's graduate student EE org), it is our pleasure to welcome you to our big welcome mixer (with free BBQ food!) between GSEE and Stanford's Optical Society (OSA)/SPIE chapter. Both GSEE and OSA have several fun events planned for the year so please join us and mingle with fellow classmates while enjoying some delicious BBQ.

 

To give us a headcount and an idea for dietary preference, please RSVP! Even if you are not planning to attend, please fill out the form especially if you want to join either the GSEE or OSA/SPIE mailing lists.

Date and Time: 
Friday, October 1, 2021 - 5:00pm
Venue: 
Packard Grove

Q-FARM Seminar: Cross-platform comparison of Arbitrary Quantum Computations

Topic: 
Cross-platform comparison of Arbitrary Quantum Computations
Abstract / Description: 

In the era of quantum advantage, when quantum computers can no longer be simulated directly by classical computers, we must find other ways to validate their performance. While algorithms such as number factoring or oracular algorithms can be easily verified, these approaches only provide pass/fail information for a single system. In this talk, I present a comparison between different quantum computers in their ability to create a given arbitrary quantum state. Looking for agreement between computers is akin to evaluating metrological standards such as disparate atomic clocks. We use randomized and correlated measurements to perform shadow tomography and compare several different quantum computers with both trapped ions and superconducting platforms included, resulting in a wealth of information on the systems. We compare several quantum states, defined by quantum circuits, and analyze the cross-platform fidelities.

Reference: arXiv:2107.11387

Date and Time: 
Thursday, September 23, 2021 - 12:15pm
Venue: 
Physics & Astrophysics Building, Room 102/103

ISL Colloquium: Interpolation Phase Transition in Neural Networks: Memorization and Generalization

Topic: 
Interpolation Phase Transition in Neural Networks: Memorization and Generalization
Abstract / Description: 

A mystery of modern neural networks is their surprising generalization power in overparametrized regime: they comprise so many parameters that they can interpolate the training set, even if actual labels are replaced by purely random ones; despite this, they achieve good prediction error on unseen data.

To demystify the above phenomena, we focus on two-layer neural networks in the neural tangent (NT) regime. Under a simple data model where n inputs are d-dimensional isotropic vectors and there are N hidden neurons, we show that as soon as Nd >> n, the minimum eigenvalue of the empirical NT kernel is bounded away from zero, and therefore the network can exactly interpolate arbitrary labels.

Next, we study the generalization error of NT ridge regression (including min-$ell_2$ norm interpolation). We show that in the same overparametrization regime Nd >> n, in terms of generalization errors, NT ridge regression is well approximated by kernel ridge regression (infinite-width kernel), which is in further we approximated by polynomial ridge regression. A surprising phenomenon is a "self-induced" regularization due to the high-degree components of the activation function.

Link to the ArXiv paper: https://arxiv.org/abs/2007.12826


This talk is hosted by the ISL Colloquium. To receive talk announcements, subscribe to the mailing list isl-colloq@lists.stanford.edu.

Date and Time: 
Thursday, September 23, 2021 - 4:30pm
Venue: 
Packard 101

Workshop in Biostatistics welcomes Moisés Expósito Alonso

Topic: 
"The genomics of climate adaptation and extinction"
Abstract / Description: 

The ongoing climate change has put a spotlight on rapid evolutionary processes that could aid species adapt to new environments. But what is the architecture of fitness across environments? Is this predictable? Can we understand genetic constraints across multiple adaptive traits? How is genetic variation loss during extinction? To address these questions we combine statistical genomics with experimental ecology and genetic engineering approaches using the plant species Arabidopsis thaliana as our experimental climate change genetics model and scaling up insights with publicly available genomes of diverse plant species.

 

Suggested Reading:
● Quantifying the scale of genetic diversity extinction in the Anthropocene
● Natural selection on the Arabidopsis thaliana genome in present and future
climates

Date and Time: 
Thursday, October 21, 2021 - 1:30pm

Workshop in Biostatistics: Big data from tiny microbes across Earth’s ecosystems

Topic: 
Big data from tiny microbes across Earth’s ecosystems
Abstract / Description: 

Genome-resolved metagenomics has enabled unprecedented insights into the ecology and evolution of environmental and host-associated microbiomes. This powerful approach is scalable and was applied to over 10,000 metagenomes collected from diverse habitats to generate an extensive catalog of microbial diversity. In collaboration with a large research consortium, we highlight how this genomic catalog can support discovery of new biosynthetic gene clusters and associating environmental viruses to their microbial hosts.

Date and Time: 
Thursday, September 30, 2021 - 1:30pm

Pages

Subscribe to RSS - Graduate