Timezone: »
- [ 65238 ] Peer Prediction for Learning Agents
- [ 65239 ] MultiGuard: Provably Robust Multi-label Classification against Adversarial Examples
- [ 65240 ] Structural Pruning via Latency-Saliency Knapsack
- [ 65241 ] On the Strong Correlation Between Model Invariance and Generalization
- [ 65243 ] Zero-Sum Stochastic Stackelberg Games
- [ 65245 ] Kantorovich Strikes Back! Wasserstein GANs are not Optimal Transport?
Q&A on RocketChat immediately following Lightning Talks
Author Information
Alexander Korotin (Skolkovo Institute of Science and Technology)
Jinyuan Jia (UIUC)
Weijian Deng (Australian National University)

I am a Computer Science PhD student at Australian National University. I focus on out-of-distribution model generalization. In my PhD research, the overall objective is Understanding Model Decision under Dynamic Testing Environments. The purpose is two-fold. The first is to provide an unsupervised way to predicate model accuracy under dynamic test scenarios. The second is to better understand the strengths and limitations of MP models. This research will significantly advance machine perception knowledge in dataset representation, model design and decision understanding
Shi Feng (IIIS, Tsinghua University)
Maying Shen (NVIDIA)
Denizalp Goktas (Brown University)
Fang-Yi Yu (George Mason University)
Alexander Kolesov (The Skolkovo Institute of Science and Technology)
Sadie Zhao (Pomona College)
Stephen Gould (ANU)
Hongxu Yin (NVIDIA)
Wenjie Qu (Huazhong University of Science and Technology)

senior undergraduate student at HUST, interested in computer security especially applied crypto and ai security. Looking for a phd position in US in 2023fall.
Liang Zheng (Australian National University)
Evgeny Burnaev (Skoltech)
Evgeny Burnaev obtained his MSc in Applied Physics and Mathematics from the Moscow Institute of Physics and Technology in 2006. After successfully defending his PhD thesis in Foundations of Computer Science at the Institute for Information Transmission Problem RAS (IITP RAS) in 2008, Evgeny stayed with the Institute as a head of IITP Data Analysis and Predictive Modeling Lab. Since 2007 Evgeny Burnaev carried out a number of successful industrial projects with Airbus, SAFT, IHI, and Sahara Force India Formula 1 team among others. The corresponding data analysis algorithms, developed by Evgeny Burnaev and his scientific group, formed a core of the algorithmic software library for metamodeling and optimization. Thanks to the developed functionality, engineers can construct fast mathematical approximations to long running computer codes (realizing physical models) based on available data and perform design space exploration for trade-off studies. The software library passed the final Technology Readiness Level 6 certification in Airbus. According to Airbus experts, application of the library “provides the reduction of up to 10% of lead time and cost in several areas of the aircraft design process”. Nowadays a spin-off company Datadvance develops a Software platform for Design Space Exploration with GUI based on this algorithmic core. Since 2016 Evgeny Burnaev works as Associate Professor of Skoltech and manages his research group for Advanced Data Analytics in Science and Engineering For his scientific achievements in the year 2017 Evgeny Burnaev was honored with the Moscow Government Prize for Young Scientists in the category for the Transmission, Storage, Processing and Protection of Information for leading the project “The development of methods for predictive analytics for processing industrial, biomedical and financial data.”
Amy Greenwald
Neil Gong (Duke University)
Pavlo Molchanov (NVIDIA)
Research scientist at NVIDIA from May 2015. Received PhD in radar target classification from Tampere University of Technology, Finland, in 2014.
Yiling Chen (Harvard University)
Lei Mao (NVIDIA)
Jianna Liu
Jose M. Alvarez (NVIDIA)
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