David Maxwell Chickering

2009
41	EE	Edith Law, Anton Mityagin, David Maxwell Chickering: Intentions: a game for classifying search query intent. CHI Extended Abstracts 2009: 3805-3810
40	EE	Paul N. Bennett, David Maxwell Chickering, Anton Mityagin: Learning consensus opinion: mining data from a labeling game. WWW 2009: 121-130
2008
39	EE	Yagil Engel, David Maxwell Chickering: Incorporating user utility into sponsored-search auctions. AAMAS (3) 2008: 1565-1568
38	EE	Ben Carterette, Paul N. Bennett, David Maxwell Chickering, Susan T. Dumais: Here or There. ECIR 2008: 16-27
37	EE	Guy Shani, David Maxwell Chickering, Christopher Meek: Mining recommendations from the web. RecSys 2008: 35-42
2007
36		Hila Becker, Christopher Meek, David Maxwell Chickering: Modeling Contextual Factors of Click Rates. AAAI 2007: 1310-1315
35	EE	David Maxwell Chickering, Tim Paek: Personalizing influence diagrams: applying online learning strategies to dialogue management. User Model. User-Adapt. Interact. 17(1-2): 71-91 (2007)
34	EE	Tim Paek, David Maxwell Chickering: Improving command and control speech recognition on mobile devices: using predictive user models for language modeling. User Model. User-Adapt. Interact. 17(1-2): 93-117 (2007)
2006
33	EE	Kumar Chellapilla, David Maxwell Chickering: Improving Cloaking Detection using Search Query Popularity and Monetizability. AIRWeb 2006: 17-23
32	EE	David Maxwell Chickering, Christopher Meek: On the incompatibility of faithfulness and monotone DAG faithfulness. Artif. Intell. 170(8-9): 653-666 (2006)
2004
31		David Maxwell Chickering, Joseph Y. Halpern: UAI '04, Proceedings of the 20th Conference in Uncertainty in Artificial Intelligence, July 7-11 2004, Banff, Canada AUAI Press 2004
30	EE	Bo Thiesson, David Maxwell Chickering, David Heckerman, Christopher Meek: ARMA Time-Series Modeling with Graphical Models. UAI 2004: 552-560
29	EE	David Maxwell Chickering, David Heckerman, Christopher Meek: Large-Sample Learning of Bayesian Networks is NP-Hard. Journal of Machine Learning Research 5: 1287-1330 (2004)
2003
28		David Maxwell Chickering, Christopher Meek, David Heckerman: Large-Sample Learning of Bayesian Networks is NP-Hard. UAI 2003: 124-133
27		Christopher Meek, David Maxwell Chickering: Practically Perfect. UAI 2003: 411-416
2002
26	EE	Christopher Meek, David Maxwell Chickering, David Heckerman: Autoregressive Tree Models for Time-Series Analysis. SDM 2002
25		David Maxwell Chickering, Christopher Meek: Finding Optimal Bayesian Networks. UAI 2002: 94-102
24	EE	David Maxwell Chickering: Learning Equivalence Classes of Bayesian-Network Structures. Journal of Machine Learning Research 2: 445-498 (2002)
23	EE	David Maxwell Chickering: Optimal Structure Identification With Greedy Search. Journal of Machine Learning Research 3: 507-554 (2002)
2001
22	EE	David Maxwell Chickering, Christopher Meek, Robert Rounthwaite: Efficient Determination of Dynamic Split Points in a Decision Tree. ICDM 2001: 91-98
21	EE	Eric Horvitz, Yongshao Ruan, Carla P. Gomes, Henry A. Kautz, Bart Selman, David Maxwell Chickering: A Bayesian Approach to Tackling Hard Computational Problems. UAI 2001: 235-244
20	EE	Andrew Zimdars, David Maxwell Chickering, Christopher Meek: Using Temporal Data for Making Recommendations. UAI 2001: 580-588
19	EE	Eric Horvitz, Yongshao Ruan, Carla P. Gomes, Henry A. Kautz, Bart Selman, David Maxwell Chickering: A Bayesian Approach to Tackling Hard Computational Problems (Preliminary Report). Electronic Notes in Discrete Mathematics 9: 376-391 (2001)
2000
18	EE	David Maxwell Chickering, David Heckerman: Targeted advertising with inventory management. ACM Conference on Electronic Commerce 2000: 145-149
17	EE	David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie: Dependency Networks for Collaborative Filtering and Data Visualization. UAI 2000: 264-273
16	EE	David Maxwell Chickering, David Heckerman: A Decision Theoretic Approach to Targeted Advertising. UAI 2000: 82-88
15	EE	David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie: Dependency Networks for Inference, Collaborative Filtering, and Data Visualization. Journal of Machine Learning Research 1: 49-75 (2000)
1999
14	EE	David Maxwell Chickering, David Heckerman: Fast Learning from Sparse Data. UAI 1999: 109-115
1998
13	EE	Bo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman: Learning Mixtures of DAG Models. UAI 1998: 504-513
1997
12	EE	David Maxwell Chickering, David Heckerman, Christopher Meek: A Bayesian Approach to Learning Bayesian Networks with Local Structure. UAI 1997: 80-89
11		David Maxwell Chickering, David Heckerman: Efficient Approximations for the Marginal Likelihood of Bayesian Networks with Hidden Variables. Machine Learning 29(2-3): 181-212 (1997)
1996
10		David Maxwell Chickering, Judea Pearl: A Clinician's Tool for Analyzing Non-Compliance. AAAI/IAAI, Vol. 2 1996: 1269-1276
9	EE	David Maxwell Chickering: Learning Equivalence Classes of Bayesian Network Structures. UAI 1996: 150-157
8	EE	David Maxwell Chickering, David Heckerman: Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network. UAI 1996: 158-168
7	EE	Richard E. Korf, David Maxwell Chickering: Best-First Minimax Search. Artif. Intell. 84(1-2): 299-337 (1996)
1995
6	EE	David Maxwell Chickering: A Transformational Characterization of Equivalent Bayesian Network Structures. UAI 1995: 87-98
5	EE	David Maxwell Chickering, Dan Geiger, David Heckerman: On Finding a Cycle Basis with a Shortest Maximal Cycle. Inf. Process. Lett. 54(1): 55-58 (1995)
4		David Heckerman, Dan Geiger, David Maxwell Chickering: Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. Machine Learning 20(3): 197-243 (1995)
1994
3		Richard E. Korf, David Maxwell Chickering: Best-First Minimax Search: Othello Results. AAAI 1994: 1365-1370
2		David Heckerman, Dan Geiger, David Maxwell Chickering: Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. KDD Workshop 1994: 85-96
1	EE	David Heckerman, Dan Geiger, David Maxwell Chickering: Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. UAI 1994: 293-301

Coauthor Index

1	Hila Becker	[36]
2	Paul N. Bennett	[38] [40]
3	Ben Carterette	[38]
4	Kumar Chellapilla	[33]
5	Susan T. Dumais	[38]
6	Yagil Engel	[39]
7	Dan Geiger	[1] [2] [4] [5]
8	Carla P. Gomes	[19] [21]
9	Joseph Y. Halpern	[31]
10	David Heckerman	[1] [2] [4] [5] [8] [11] [12] [13] [14] [15] [16] [17] [18] [26] [28] [29] [30]
11	Eric Horvitz	[19] [21]
12	Carl Myers Kadie	[15] [17]
13	Henry A. Kautz	[19] [21]
14	Richard E. Korf	[3] [7]
15	Edith Law	[41]
16	Christopher Meek	[12] [13] [15] [17] [20] [22] [25] [26] [27] [28] [29] [30] [32] [36] [37]
17	Anton Mityagin	[40] [41]
18	Tim Paek	[34] [35]
19	Judea Pearl	[10]
20	Robert Rounthwaite	[15] [17] [22]
21	Yongshao Ruan	[19] [21]
22	Bart Selman	[19] [21]
23	Guy Shani	[37]
24	Bo Thiesson	[13] [30]
25	Andrew Zimdars	[20]

Colors in the list of coauthors