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Function Approximation, Probabilistic View Point, Deterministic View Point.

This video series explains concepts from the book "Deep Learning" by Aaron Courville, Ian Goodfellow, and Yoshua Bengio.

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Score-based diffusion models, while achieving remarkable empirical performance, often suffer from low sampling speed, due to ...

Time: October 1, 2025 Speaker: Jiawei Zhang (UW-Madison) Abstract: It is well known that for nonconvex unconstrained ...

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Although asynchronous session subtyping is undecidable in general, we can rely on practical approximate algorithms. I will briefly ...

Unsupervised learning is a central challenge in artificial intelligence, lying at the intersection of statistics and machine learning.

This tutorial brings together two rapidly developing topics in modern statistical learning: (i) synthetic data methods for imbalanced ...

Random Experiment, Probability Triplet.

Complete Introduction to Deep Learning: Mathematical Foundations & Intuition Join Dr. Heman Shakeri for a comprehensive ...

MIT 15.773 Hands-On Deep Learning Spring 2024 Instructor: Rama Ramakrishnan View the complete course: ...

In this video, we complete the binary quantum state discrimination pipeline by deriving, implementing, and numerically verifying ...

TITLE: Randomized Linear Algebra with Subspace Injections SPEAKER: Joel Tropp (Caltech) ABSTRACT: To achieve the ...

Neural Networks for Computer Vision and Natural Language Processing Course URL: ...

We get back to K-means clustering algorithm. This time we define the underlying learning problem through risk formulation.

Date : 06 Jan 2026 Abstract: The algorithmic study of market equilibria has been a cornerstone of economics and computation ...

I will overview several practical tricks for handling (interpolating) functions efficiently, and discuss how they can help your ...

... widely used in network security, optimization, resource allocation, and approximation algorithms. This lecture is useful for B.Sc., ...