Search for tag: "arc colloquium"

57 Media

Vidya Muthukumar - Surprises in overparameterized… duration 57 minutes 41 seconds Vidya Muthukumar - Surprises in overparameterized… Vidya Muthukumar - Surprises in overparameterized linear classification	Vidya Muthukumar - Surprises in overparameterized linear classification Seemingly counter-intuitive phenomena in deep neural networks and kernel methods have prompted a recent re-investigation of classical machine learning methods, like linear models. Of particular focus… algorithms and randomness center +4 More From Katie Gentilello 10 plays 0 name Vidya Muthukumar Date October 25th, 2021
Anupam Gupta - Finding and Counting k-cuts in… duration 58 minutes 53 seconds Anupam Gupta - Finding and Counting k-cuts in… Anupam Gupta - Finding and Counting k-cuts in Graphs	Anupam Gupta - Finding and Counting k-cuts in Graphs For an undirected graph with edge weights, a k-cut is a set of edges whose deletion breaks the graph into at least k connected components. How fast can we find a minimum-weight k-cut? And how many… arc colloquium +4 More From Katie Gentilello 17 plays 0 name Anupam Gupta Date October 18th, 2021
Aaron Sidford - Recent Advances on the Maximum… duration 1 hour 6 minutes Aaron Sidford - Recent Advances on the Maximum… Aaron Sidford - Recent Advances on the Maximum Flow Problem	Aaron Sidford - Recent Advances on the Maximum Flow Problem The maximum flow problem is an incredibly well-studied problem in combinatorial optimization. The problem encompasses a range of cut, matching, and scheduling problems and is a key a proving ground… arc colloquium +4 More From Katie Gentilello 20 plays 0 name Aaron Sidford Date October 4th, 2021
Maryam Aliakbarpour - Distribution testing: … duration 44 minutes 54 seconds Maryam Aliakbarpour - Distribution testing: … Maryam Aliakbarpour - Distribution testing: Classical and new paradigms	Maryam Aliakbarpour - Distribution testing: Classical and new paradigms One of the most fundamental problems in learning theory is to view input data as random samples from an unknown distribution and then to make statistical inferences about the underlying distribution.… arc colloquium +4 More From Katie Gentilello 31 plays 0 name Maryam Aliakbarpour Date March 2nd, 2020
Vedat Levi Alev - Improved Analysis of Higher… duration 53 minutes 36 seconds Vedat Levi Alev - Improved Analysis of Higher… Vedat Levi Alev - Improved Analysis of Higher Order Random Walks and Applications	Vedat Levi Alev - Improved Analysis of Higher Order Random Walks and Applications Local spectral expansion is a very useful method for arguing about the spectral properties of several random walk matrices over simplicial complexes. The motivation of this work is to extend this… arc colloquium +4 More From Katie Gentilello 69 plays 0 name Vedat Levi Alev Date February 10th, 2020
Kuikui Liu - Spectral Independence in… duration 57 minutes 12 seconds Kuikui Liu - Spectral Independence in… Kuikui Liu - Spectral Independence in High-Dimensional Expanders and Applications to the Hardcore Model	Kuikui Liu - Spectral Independence in High-Dimensional Expanders and Applications to the Hardcore Model We say a probability distribution µ is spectrally independent if an associated correlation matrix has a bounded largest eigenvalue for the distribution and all of its conditional distributions.… algorithms and randomness center +4 More From Katie Gentilello 28 plays 0 name Kuikui Liu Date January 27th, 2020
Samuel Hopkins - Robust Mean Estimation in… duration 56 minutes 44 seconds Samuel Hopkins - Robust Mean Estimation in… Samuel Hopkins - Robust Mean Estimation in Nearly-Linear Time	Samuel Hopkins - Robust Mean Estimation in Nearly-Linear Time Robust mean estimation is the following basic estimation question: given i.i.d. copies of a random vector X in d-dimensional Euclidean space of which a small constant fraction are corrupted, how well… arc colloquium +4 More From Katie Gentilello 17 plays 0 name Samuel Hopkins Date December 2nd, 2019
Jelani Nelson - Some new approaches to the heavy… duration 1 hour 0 minutes Jelani Nelson - Some new approaches to the heavy… Jelani Nelson - Some new approaches to the heavy hitters problem	Jelani Nelson - Some new approaches to the heavy hitters problem In the 'frequent items' problem one sees a sequence of items in a stream (e.g. a stream of words coming into a search query engine likeGoogle) and wants to report a small list of items… arc colloquium +4 More From Katie Gentilello 22 plays 0 name Jelani Nelson Date September 16th, 2019
Yuhao Yi - Fast Approximation Algorithms and… duration 57 minutes 21 seconds Yuhao Yi - Fast Approximation Algorithms and… Yuhao Yi - Fast Approximation Algorithms and Complexity Analysis for Design of Networked Systems	Yuhao Yi - Fast Approximation Algorithms and Complexity Analysis for Design of Networked Systems This talk focuses on network design algorithms for optimizing average consensus dynamics, dynamics that are widely used for information diﬀusion and distributed coordination in networked control… arc colloquium +4 More From Katie Gentilello 15 plays 0 name Yuhao Yi Date November 18th, 2019
Nima Anari - Rapidly Mixing Random Walks via… duration 1 hour 41 minutes Nima Anari - Rapidly Mixing Random Walks via… Nima Anari - Rapidly Mixing Random Walks via Log-Concave Polynomials (Part 2)	Nima Anari - Rapidly Mixing Random Walks via Log-Concave Polynomials (Part 2) (This is Part 2, continuation of Tuesday's lecture.)A fundamental tool used in sampling, counting, and inference problems is the Markov Chain Monte Carlo method, which uses random walks to solve… algorithms and randomness center +4 More From Katie Gentilello 38 plays 0 name Nima Anari Date November 6th, 2019
Nima Anari - Rapidly Mixing Random Walks via… duration 1 hour 26 minutes Nima Anari - Rapidly Mixing Random Walks via… Nima Anari - Rapidly Mixing Random Walks via Log-Concave Polynomials (Part 1)	Nima Anari - Rapidly Mixing Random Walks via Log-Concave Polynomials (Part 1) A fundamental tool used in sampling, counting, and inference problems is the Markov Chain Monte Carlo method, which uses random walks to solve computational problems. The main parameter defining the… arc colloquium +4 More From Katie Gentilello 56 plays 0 name Nima Anari Date November 5th, 2019
Ravi Kumar - Algorithmic Discrete Choice duration 49 minutes 5 seconds Ravi Kumar - Algorithmic Discrete Choice Ravi Kumar - Algorithmic Discrete Choice	Ravi Kumar - Algorithmic Discrete Choice In this talk we consider random utility models for discrete choice. In discrete choice, the task is to select exactly one element from a discrete set of alternatives. We focus on algorithmic… algorithms and randomness center +4 More From Katie Gentilello 16 plays 0 name Ravi Kumar Date November 4th, 2019
Rong Ge - What 2-layer neural nets can we… duration 55 minutes 49 seconds Rong Ge - What 2-layer neural nets can we… Rong Ge - What 2-layer neural nets can we optimize?	Rong Ge - What 2-layer neural nets can we optimize? Optimizing neural networks is a highly nonconvex problem, and even optimizing a 2-layer neural network can be challenging. In the recent years many different approaches were proposed to learn 2-layer… arc colloquium +4 More From Katie Gentilello 31 plays 0 name Rong Ge Date October 28th, 2019
Umang Bhaskar - Partial Function Extension with… duration 56 minutes 41 seconds Umang Bhaskar - Partial Function Extension with… Umang Bhaskar - Partial Function Extension with Applications to Learning and Property Testing	Umang Bhaskar - Partial Function Extension with Applications to Learning and Property Testing In partial function extension, we are given a partial function consisting of points from a domain and a function value at each point.Our objective is to determine if this partial function can be… arc colloquium +4 More From Katie Gentilello 2 plays 0 name Umang Bhaskar Date October 18th, 2019
Thomas Rothvoss - Linear Size Sparsifier and the… duration 55 minutes 21 seconds Thomas Rothvoss - Linear Size Sparsifier and the… Thomas Rothvoss - Linear Size Sparsifier and the Geometry of the Operator Norm Ball	Thomas Rothvoss - Linear Size Sparsifier and the Geometry of the Operator Norm Ball The Matrix Spencer Conjecture asks whether given n symmetric matrices in ℝn×n with eigenvalues in [−1,1] one can always find signs so that their signed sum has singular values bounded by… algorithms and randomness center +4 More From Katie Gentilello 45 plays 0 name Thomas Rothvoss Date October 7th, 2019
Nikhil Devanur - Lagrangian Duality in Mechanism… duration 57 minutes 29 seconds Nikhil Devanur - Lagrangian Duality in Mechanism… Nikhil Devanur - Lagrangian Duality in Mechanism Design	Nikhil Devanur - Lagrangian Duality in Mechanism Design This talk surveys the usage of Lagrangian Duality in the design and analysis of auctions. Designing optimal (revenue maximizing) auctions in multi-parameter settings has been among the most active… arc colloquium +4 More From Katie Gentilello 24 plays 0 name Nikhil Devanur Date September 30th, 2019