Get on target: How individually synthesized capture probes will enrich your NGS experiments
Learn how IDT's individually synthesized and ESI-MS QC'ed capture probes offer an affordable solution resulting in higher uniformity of coverage, improved ...
Integrated DNA Technologies
Dynamical, symplectic and stochastic perspectives on optimization – Michael Jordan – ICM2018
Plenary Lecture 20 Dynamical, symplectic and stochastic perspectives on gradient-based optimization Michael Jordan Abstract: Our topic is the relationship ...
Rio ICM2018
Stochastic Approximation and Reinforcement Learning: Hidden Theory and New Super-Fast Algorithms
Stochastic approximation algorithms are used to approximate solutions to fixed point equations that involve expectations of functions with respect to possibly ...
Microsoft Research
Lecture 6. Introduction to Bayesian Statistics, Exponential Family of Distributions
Parametric modeling, Sufficiency principle, Likelihood principle, Stopping rules, Conditionality principle, p-values and issues with frequentist statistics, MLE and ...
Scientific Computing and Artificial Intelligence
MIT CompBio Lecture 02 - DynamicProgramming (Part1)
MIT Computational Biology: Genomes, Networks, Evolution, Health Prof. Manolis Kellis http://compbio.mit.edu/6.047/ Fall 2018 Computational, Biology, ...
Manolis Kellis
Markov Chains - Part 1
Thanks to all of you who support me on Patreon. You da real mvps! $1 per month helps!! :) https://www.patreon.com/patrickjmt !! Part 2: ...
patrickJMT
The Natural Mathematics Arising in Information Theory and Investment
Prof. Tom Cover Stanford University October 20, 2008 -_-_-_-_-_-_-_-_-_-_-_- Prestige Lecture Series on Science of Information Sponsored by the Purdue ...
Purdue University
Emilie Kaufmann - Optimal Best Arm Identification with Fixed Confidence
This talk proposes a complete characterization of the complexity of best-arm identification in one-parameter bandit models. We first give a new, tight lower bound ...
Institut des Hautes Études Scientifiques (IHÉS)
On the Hardness of Reinforcement Learning With Value-function Approximation
Nan Jiang (University of Illinois Urbana-Champaign) https://simons.berkeley.edu/talks/tba-86 Emerging Challenges in Deep Learning.
Simons Institute
Aaditya Ramdas on Exponential line-crossing inequalities
CMU Theory lunch talk from April 03, 2019 by Aaditya Ramdas on Exponential line-crossing inequalities This talk will present a class of exponential bounds for ...
CMU Theory
Dimitri Bertsekas: "Distributed and Multiagent Reinforcement Learning"
Intersections between Control, Learning and Optimization 2020 "Distributed and Multiagent Reinforcement Learning" Dimitri Bertsekas - Massachusetts Institute ...
Institute for Pure & Applied Mathematics (IPAM)
Deep RL Bootcamp Lecture 4A: Policy Gradients
Instructor: Pieter Abbeel Lecture 4A Deep RL Bootcamp Berkeley August 2017 Policy Gradients.
AI Prism
Applied Machine Learning 2019 - Lecture 13 - Parameter Selection and Automatic Machine Learning
Grid Search, Randomized Search Bayesian Optimization, SMBO Successive halving, hyperband auto-sklearn Freely borrowed materials from ...
Andreas Mueller
The Latest Developments in Cryptography Webinar
Learn more at https://online.stanford.edu. In this webinar, you'll learn the latest on all things “crypto” from Professor Dan Boneh, head of the Stanford's applied ...
stanfordonline
MIT CompBio Lecture 19 - Phylogenetics
MIT Computational Biology: Genomes, Networks, Evolution, Health Prof. Manolis Kellis http://compbio.mit.edu/6.047/ Fall 2018 Lecture 18 - Phylogenetics 0.
Manolis Kellis
First-Order Stochastic Optimization
Rachel Ward, University of Texas at Austin https://simons.berkeley.edu/talks/clone-intro-his-foundations-data-science-book-ii-1 Foundations of Data Science ...
Simons Institute
Towards Generalization and Efficiency in Reinforcement Learning
In classic supervised machine learning, a learning agent behaves as a passive observer: it receives examples from some external environment which it has no ...
Microsoft Research
L2 Autoregressive Models -- CS294-158-SP20 Deep Unsupervised Learning -- UC Berkeley, Spring 2020
Instructor: Pieter Abbeel Course Instructors: Pieter Abbeel, Peter Chen, Jonathan Ho, Aravind Srinivas, Alexander Li, Wilson Yan Course Website: ...
Pieter Abbeel
The Rise and Decline of Nations and Civilizations
Updated version can be seen here - http://www.youtube.com/watch?v=UZ1c1qL18JM Speakers: Jared Diamond, Professor, Department of Geography, ...
Milken Institute
Synthetic Antibodies - The Emerging Field of "Aptamers" in Diagnostics and Drug Discovery
Presented At: LabRoots - Drug Discovery Virtual Event 2019 Presented By: G. Thomas Caltagirone, PhD - President & CEO, Aptagen, LLC Speaker Biography: ...
LabRoots
TutORial: Bayesian Optimization
By Peter Frazier. Bayesian optimization is widely used for tuning deep neural networks and optimizing other black-box objective functions that take a long time to ...
INFORMS
Invited Talk: Post-selection Inference for Forward Stepwise Regression, Lasso and other procedures
In this talk I will present new inference tools for adaptive statistical procedures. These tools provide p-values and confidence intervals that have correct ...
Microsoft Research
Boosting Simple Learners - Shay Moran
Seminar on Theoretical Machine Learning Topic: Boosting Simple Learners Speaker: Shay Moran Affiliation: Google Date: May 5, 2020 For more video please ...
Institute for Advanced Study
Ross Taylor | Time Series for Python with PyFlux
PyData SF 2016 PyFlux is a new library for time series analysis for Python. It brings together a vast array of time series models, including recent models such as ...
PyData
Debiasing Evidence Approximations: Importance-Weighted Autoencoders Jackknife Variational Inference
The importance-weighted autoencoder (IWAE) approach of Burda et al. (2015) defines a sequence of increasingly tighter bounds on the marginal likelihood of ...
Microsoft Research
Deep Learning 7. Attention and Memory in Deep Learning
Alex Graves, Research Scientist, discusses attention and memory in deep learning as part of the Advanced Deep Learning & Reinforcement Learning Lectures.
DeepMind
Classical Algorithms for Quantum Mean Values
Sergey Bravyi (IBM T.J. Watson Research Center) https://simons.berkeley.edu/talks/classical-algorithms-quantum-mean-values-0 Quantum Devices: Simulation, ...
Simons Institute
"Randomized Gossip Methods" by Dahlia Malkhi
Info: https://pwlconf.org/2016/dahlia-malkhi/ Slides: http://bit.ly/2cC59Ml Transcription: http://bit.ly/2y8XH5U Dahlia's Site: https://dahliamalkhi.wordpress.com/ ...
PapersWeLove
Approximate nearest neighbor search in high dimensions – Piotr Indyk – ICM2018
Mathematical Aspects of Computer Science Invited Lecture 14.7 Approximate nearest neighbor search in high dimensions Piotr Indyk Abstract: The nearest ...
Rio ICM2018
The Case for Continuous Time
Time is a continuous quantity. This talk begins with theoretical and experimental problems that arise when time is treated as a discrete quantity in stochastic ...
Microsoft Research
Congressman Heck Town Hall with Dr. Trevor Bedford
Dr. Bedford discusses the course of the coronavirus outbreak and looks at what may lie ahead. Visit us online: https://www.fredhutch.org/en.html Follow us on ...
Fred Hutch
Data Science in Cyber-Security and Related Statistical Challenges
Data science techniques have an important role to play in the next generation of cyber-security defenses. Inside a typical enterprise computer network, a number ...
Microsoft Research
Jacob Schreiber | Pomegranate: fast and flexible probabilistic models in python
PyData Chicago 2016 Slides: http://www.slideshare.net/secret/cxZTghInOlIeOs pomegranate is a python module for probabilistic modelling focusing on both ...
PyData
MIT CompBio Lecture 03 - Database Search
MIT Computational Biology: Genomes, Networks, Evolution, Health Prof. Manolis Kellis http://compbio.mit.edu/6.047/ Fall 2018 Computational, Biology, ...
Manolis Kellis
Resilience and Security in Cyber-Physical Systems: Self-Driving Cars and Smart Devices
The future will be defined by autonomous computer systems that are tightly integrated with the environment, also known as Cyber-Physical systems (CPS).
Microsoft Research
Validating differential gene expression: Methods, Sarah Diermeier, Ph.D.
Dr. Diermeier, post-doctoral fellow, CSHL gives a lecture on "Validating RNA-Seq data by qRT-PCR"
DNA Learning Center
data@breakfast: Prof Tulio de Oliveira “COVID-19 Genomics and Epidemiology”
Data@Breakfast is an initiative of the University of KwaZulu-Natal (UKZN) Big Data and Informatics Research Flagship. Traditionally it takes place on the last ...
UKZN Data at Breakfast
NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: Real time data...
Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: Real time data sketches by Alex Smola Alex is a ...
GoogleTechTalks
Experimental Evolution: 50,000 Generations in the Life of E. coli
Air date: Wednesday, October 13, 2010, 3:00:00 PM Time displayed is Eastern Time, Washington DC Local Category: Wednesday Afternoon Lectures ...
NIH VideoCast
Divide-And-Conquer Hybrid Methods for Smaller Quantum Computers
Vedran Dunjko (University of Leiden) https://simons.berkeley.edu/talks/divide-and-conquer-hybrid-methods-smaller-quantum-computers Quantum Devices: ...
Simons Institute
Diseases that affect us most
3:05 - Introduction from Professor Chris Goodnow 17:40 - Dr David Gallego-Ortega - Development of new generation breast cancer therapies 24:11 - Dr Joanna ...
Garvan Institute of Medical Research
Robert FREY - 180 years of Market Drawdowns
Friends of IHES held the Mathematical Finance colloquium “An Analysis of 180 Years of Market Drawdowns” on 30 June 2015 at 6.00 pm in New York, ...
Institut des Hautes Études Scientifiques (IHÉS)
