Probabilistic Retrieval: Practical Relevance Feedback

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (32)

Page 2 of 4

Explores pretraining models like BERT, T5, and GPT, discussing their training objectives and applications in natural language processing.

Biological structure and function emerge from unsupervised learning

Delves into how biological structure and function are decoded through unsupervised learning of protein sequences.

Integrative Benchmarking: Advancing System Models of Human Intelligence

Explores advancing system models of human intelligence through integrative benchmarking and the importance of Brain-Score for fair model comparisons.

Information retrieval: vector space

Covers the basics of information retrieval using vector space models and practical exercises on relevance feedback and posting list scanning.

Fundamental Limits of Gradient-Based Learning

Delves into the fundamental limits of gradient-based learning on neural networks, covering topics such as binomial theorem, exponential series, and moment-generating functions.

Latent Semantic Indexing

Covers Latent Semantic Indexing, word embeddings, and the skipgram model with negative sampling.

Joint Equidistribution of CM Points

Covers the joint equidistribution of CM points and the ergodic decomposition theorem in compact abelian groups.

Optimal Decision Making with CVXPY

Introduces CVXPY for optimal decision making through atomic functions and operators.

Latent Semantic Indexing: Concepts and Applications

Explores Latent Semantic Indexing, a technique for mapping documents into a concept space for retrieval and classification.

Node Degree and Strength

Explores node degree and strength in network neuroscience, discussing random vs real networks and the challenges of fitting power laws to real data.