CS 510: Advanced Information Retrieval (Fall 2017)

Instructor: ChengXiang Zhai

Schedule (anticipated)

Notes:

Date Topic and Readings Notes
08/29 Tue Course Overview; Overview of Text Retrieval and Analysis (slides)
08/31 Thu Basic Probability & Statistics (slides)
Readings: Rosenfeld’s note on estimation
Assign #1 released
09/05 Tue Basic Concepts of Information Theory (slides)
Readings: Rosenfeld’s note on information theory
Assign #2 released
09/07 Thu Overview of Statistical Language Models (slides)
Readings: Two decades of statistical language modeling
Assign #1 due 9/9
09/12 Tue N-gram Language Models I (slides)
Readings: Chen and Goodman’s empirical study of smoothing, (optional) Heafield’s slides on n-gram LMs
09/14 Thu N-gram Language Models II (slides)
Readings: Chen and Goodman’s empirical study of smoothing, (optional) Heafield’s slides on n-gram LMs
Assign #2 due; Assign #3 released
09/19 Tue Language Models for Text Retrieval I (slides)
Readings: BM25, Review of IR models (book chapter2)
09/21 Thu Language Models for Text Retrieval II (slides)
Readings: RSJ Model Derivation Note, Study of smoothing for IR
Assign #3 due; Assign #4 released; MP1 released
09/26 Tue Language Models for Text Retrieval III (slides)
Readings: Model-based feedback
09/28 Thu Class-based N-gram Language Models (Lecture by Chase Geigle) (slides)
Readings: Brown Clustering, Alternate Brown Clustering Derivation
Assign #4 due
10/03 Tue Word Embeddings (Lecture by Chase Geigle) (slides)
Readings: word2vec, word2vec reduction, GloVe, Embedding Hyperparameters
MP1 due; MP2 released
10/05 Thu Midterm Exam I (covering Assign #1–#4)
10/10 Tue Mixture Language Models I (slides)
Readings: Chapter 17. Topic Analyisis
10/12 Thu Mixture Language Models II (slides)
Readings: Chapter 17. Topic Analyisis, PLSA note, EM note one, EM note two
Assign #5 released; MP3 released; MP2 due 10/13
10/17 Tue Mixture Language Models III (slides)
Readings: Chapter 17. Topic Analyisis, PLSA note, EM note one, EM note two
Project proposals due
10/19 Thu Bayesian Inference for Mixture Language Models I (slides)
Assign #5 due; Assign #6 released
10/24 Tue Bayesian Inference for Mixture Language Models II (slides)
Readings: Inference Methods for LDA
10/26 Thu Bayesian Inference for Mixture Language Models III (slides)
Readings: Inference Methods for LDA
Assign #6 due; Assign #7 released
10/31 Tue Bayesian Inference for Mixture Language Models IV (slides)
Readings: Inference Methods for LDA, Gibbs Sampling for the Uninitiated
11/02 Thu Hidden Markov Models I (slides)
Readings: The classic Rabiner tutorial on HMM, Note on HMM
Assign #7 due; MP4 released
11/07 Tue Hidden Markov Models II (slides)
Readings: The classic Rabiner tutorial on HMM, Note on HMM
MP3 due
11/09 Thu Midterm Exam II (covering Assign #5–#7)
11/14 Tue Hidden Markov Models II (slides)
Readings: The classic Rabiner tutorial on HMM, Note on HMM
11/16 Thu Learning to Rank (Lecture by Santu Karmaker) (slides)
Readings: Hang Li’s notes on Learning to Rank, LambdaMART paper
11/21 Tue Thanksgiving Break
[MP4] (mp4.html) due
11/23 Thu Thanksgiving Break
11/28 Tue Contextualized Language Model
11/30 Thu Deep Learning
Project progress presentations due 12/2
12/05 Tue Neural Language Models
12/07 Thu TBA
12/12 Tue TBA
12/14 Thu Reading Day
12/15 Fri Final Exams Begin
12/19 Tue Final project reports due