CS 221: Artificial Intelligence: Principles and Techniques
Artificial intelligence (AI) has had a huge impact in many areas, including medical diagnosis, speech recognition, robotics, web search, advertising, and scheduling. This course focuses on the foundational concepts that drive these applications. In short, AI is the mathematics of making good decisions given incomplete information (hence the need for probability) and limited computation (hence the need for algorithms). Specific topics include search, constraint satisfaction, game playing, Markov decision processes, graphical models, machine learning, and logic. Prerequisites:
CS 103 or
CS 103B/X,
CS 106B or
CS 106X,
CS 107, and
CS 109 (algorithms, probability, and programming experience).
Terms: Aut, Spr, Sum
| Units: 3-4
Instructors:
Charikar, M. (PI)
;
Jia, R. (PI)
;
Liang, P. (PI)
;
Sadigh, D. (PI)
;
Amidi, S. (TA)
;
Baby, S. (TA)
;
Bakst, W. (TA)
;
Balachandar, N. (TA)
;
Barbier, N. (TA)
;
Chen, J. (TA)
;
Dhoot, A. (TA)
;
Diamond, S. (TA)
;
Diehl Martinez, R. (TA)
;
Dong, S. (TA)
;
Effron, A. (TA)
;
Fu, A. (TA)
;
Golub, D. (TA)
;
Gupta, A. (TA)
;
Han, A. (TA)
;
Hoffman, J. (TA)
;
Hsu, V. (TA)
;
Kabaghe, C. (TA)
;
Kamath, A. (TA)
;
Laloudakis, Y. (TA)
;
Lee, J. (TA)
;
Li, Y. (TA)
;
Liu, K. (TA)
;
Mani, N. (TA)
;
Patel, V. (TA)
;
Petit, B. (TA)
;
Qin, Z. (TA)
;
Saleh, M. (TA)
;
Selsam, D. (TA)
;
Seshadri, S. (TA)
;
Shah, C. (TA)
;
Sohmshetty, A. (TA)
;
Sriram, P. (TA)
;
Srivastava, M. (TA)
;
Wang, H. (TA)
;
Wang, Z. (TA)
;
Wu, Y. (TA)
;
Zhou, B. (TA)
;
Zhu, A. (TA)
CS 224U: Natural Language Understanding (LINGUIST 188, LINGUIST 288)
Project-oriented class focused on developing systems and algorithms for robust machine understanding of human language. Draws on theoretical concepts from linguistics, natural language processing, and machine learning. Topics include lexical semantics, distributed representations of meaning, relation extraction, semantic parsing, sentiment analysis, and dialogue agents, with special lectures on developing projects, presenting research results, and making connections with industry. Prerequisites: one of
LINGUIST 180,
CS 124,
CS 224N,
CS224S, or
CS221; and logical/semantics such as
LINGUIST 130A or B,
CS 157, or
PHIL150
Terms: Spr
| Units: 3-4
Instructors:
MacCartney, B. (PI)
;
Potts, C. (PI)
;
Bhaskaran, J. (TA)
...
more instructors for CS 224U »
Instructors:
MacCartney, B. (PI)
;
Potts, C. (PI)
;
Bhaskaran, J. (TA)
;
Farhangi, A. (TA)
;
Geiger, A. (TA)
;
Kim, M. (TA)
;
Li, L. (TA)
;
Wang, C. (TA)
;
Yerukola, A. (TA)
;
Zhou, X. (TA)
CS 332: Advanced Survey of Reinforcement Learning
This class will provide a core overview of essential topics and new research frontiers in reinforcement learning. Planned topics include: model free and model based reinforcement learning, policy search, Monte Carlo Tree Search planning methods, off policy evaluation, exploration, imitation learning, temporal abstraction/hierarchical approaches, safety and risk sensitivity, human-in-the-loop RL, inverse reinforcement learning, learning to communicate, and insights from human learning. Students are expected to create an original research paper on a related topic. Prerequisites: CS221 or
AA238/CS238 or CS234 or CS229 or similar experience.
Terms: Aut
| Units: 3
Instructors:
Brunskill, E. (PI)
;
Zanette, A. (TA)
LINGUIST 188: Natural Language Understanding (CS 224U, LINGUIST 288)
Project-oriented class focused on developing systems and algorithms for robust machine understanding of human language. Draws on theoretical concepts from linguistics, natural language processing, and machine learning. Topics include lexical semantics, distributed representations of meaning, relation extraction, semantic parsing, sentiment analysis, and dialogue agents, with special lectures on developing projects, presenting research results, and making connections with industry. Prerequisites: one of
LINGUIST 180,
CS 124,
CS 224N,
CS224S, or
CS221; and logical/semantics such as
LINGUIST 130A or B,
CS 157, or
PHIL150
Terms: Spr
| Units: 3-4
Instructors:
MacCartney, B. (PI)
;
Potts, C. (PI)
;
Bhaskaran, J. (TA)
...
more instructors for LINGUIST 188 »
Instructors:
MacCartney, B. (PI)
;
Potts, C. (PI)
;
Bhaskaran, J. (TA)
;
Farhangi, A. (TA)
;
Geiger, A. (TA)
;
Kim, M. (TA)
;
Li, L. (TA)
;
Wang, C. (TA)
;
Yerukola, A. (TA)
;
Zhou, X. (TA)
LINGUIST 288: Natural Language Understanding (CS 224U, LINGUIST 188)
Project-oriented class focused on developing systems and algorithms for robust machine understanding of human language. Draws on theoretical concepts from linguistics, natural language processing, and machine learning. Topics include lexical semantics, distributed representations of meaning, relation extraction, semantic parsing, sentiment analysis, and dialogue agents, with special lectures on developing projects, presenting research results, and making connections with industry. Prerequisites: one of
LINGUIST 180,
CS 124,
CS 224N,
CS224S, or
CS221; and logical/semantics such as
LINGUIST 130A or B,
CS 157, or
PHIL150
Terms: Spr
| Units: 3-4
Instructors:
MacCartney, B. (PI)
;
Potts, C. (PI)
;
Bhaskaran, J. (TA)
...
more instructors for LINGUIST 288 »
Instructors:
MacCartney, B. (PI)
;
Potts, C. (PI)
;
Bhaskaran, J. (TA)
;
Farhangi, A. (TA)
;
Geiger, A. (TA)
;
Kim, M. (TA)
;
Li, L. (TA)
;
Wang, C. (TA)
;
Yerukola, A. (TA)
;
Zhou, X. (TA)
Filter Results: