Unsupervised Deep Learning: Why Learn Without a Teacher - Tutorial
On 15 Jun, 2021 By admin 0 Comments
External Course
Unsupervised Deep Learning: Types of Learning - Tutorial
On 15 Jun, 2021 By admin 0 Comments
Unsupervised Deep Learning - Tutorial
On 15 Jun, 2021 By admin 0 Comments
The Peril of Politicizing Science
On 14 Jun, 2021 By admin 0 Comments
DSA ADS Course - 2021
The Peril of Politicizing Science
Bayesian Inference in Monte Carlo Tree Search
On 10 Jun, 2021 By admin 0 Comments
DSA External Course
Building Machines That Learn and Think Like People
On 10 Jun, 2021 By admin 0 Comments
2016
DSA ADS Course - 2021
Abstract:
Course in Functional Analysis - Conway
On 8 Jun, 2021 By admin 0 Comments
DSA ADS Course - 2021
A Course in Functional Analysis - Conway
Conway spells out the notion of a strict inductive limit of locally convex spaces, which is the only systematic way of talking about test functions and distributions. Chapter V, on weak topologies, is excellent, and proves, for example, the Banach-Alaoglu theorem, the Krein-Milman theorem, and proves (following de Branges) the Stone-Weierstrass theorem using the Krein-Milman theorem.
Fundamentals of Functional Analysis
On 8 Jun, 2021 By admin 0 Comments
DSA ADS Course - 2021
Fundamentals of Functional Analysis
Basic one-year course in functional analysis.
Functional analysis plays a crucial role in the applied sciences and focuses on general topology, vector spaces, banach spaces and hilbert spaces.
Algorithms for Inverse Reinforcement Learning
On 7 Jun, 2021 By admin 0 Comments
DSA ADS Course - 2021
ICML '00: Proceedings of the Seventeenth International Conference on Machine LearningJune 2000 Pages 663–670
The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence
On 7 Jun, 2021 By admin 0 Comments
2020
DSA ADS Course - 2021
Recent research in artificial intelligence and machine learning has largely emphasized general-purpose learning and ever-larger training sets and more and more compute. In contrast, I propose a hybrid, knowledge-driven, reasoning-based approach, centered around cognitive models, that could provide the substrate for a richer, more robust AI than is currently possible.