Enterprise Search Relevance at Box: Simplicity
Explore Box's approach to delivering relevant search results across diverse enterprises using Solr and TensorFlow Ranking, balancing simplicity with privacy and security.
Extracting Speaker and Emotion Information from Self-Supervised Speech Models
Explore techniques for extracting speaker and emotion data from self-supervised speech models, enhancing speech recognition and analysis capabilities.
Probabilistic Linear Discriminant Analysis of i-Vector Posterior Distributions
Explore probabilistic linear discriminant analysis for i-vector posterior distributions in speaker recognition, enhancing understanding of advanced speech processing techniques.
The Platonic Representation Hypothesis
Explore the Platonic Representation Hypothesis with MIT's Phillip Isola, delving into philosophical concepts and their applications in modern computational theory.
Tensor Network for Machine Learning Applications - Lecture 3
Explore advanced tensor network techniques for machine learning, focusing on applications and practical implementations in data analysis and modeling.
Tensor Network for Machine Learning Applications - Lecture 1
Explore tensor networks' applications in machine learning, focusing on their potential to enhance computational efficiency and model complexity.
Towards Monosemanticity: Decomposing Language Models with Dictionary Learning
Explore monosemanticity in neural networks through sparse autoencoders. Learn how extracting interpretable features enhances understanding of language model behavior and improves reasoning capabilities.
UBM-based Acoustic Modeling for ASR - 2009
Explore advanced UBM-based acoustic modeling techniques for automatic speech recognition, enhancing ASR system performance and accuracy.
An Implementation of Sub-Space Model Based Automatic Speech Recognition - 2009
Explore advanced speech recognition techniques using sub-space models in this in-depth implementation guide from Johns Hopkins University's CLSP.
Spectral Learning
Explore spectral learning techniques and their applications in machine learning and data analysis with Lorenzo Chicchi's comprehensive lecture.