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ORCIDDavid Maxwell Chickering
Max Chickering
Person information
- affiliation: Microsoft Research
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2020 – today
- 2020
[c44]Max Chickering:
Statistically Efficient Greedy Equivalence Search. UAI 2020: 241-249
2010 – 2019
- 2017
- [c43]Paul N. Bennett, David Maxwell Chickering, Christopher Meek, Xiaojin Zhu:
Algorithms for Active Classifier Selection: Maximizing Recall with Precision Constraints. WSDM 2017: 711-719 - [i22]Patrice Y. Simard, Saleema Amershi, David Maxwell Chickering, Alicia Edelman Pelton, Soroush Ghorashi, Christopher Meek, Gonzalo A. Ramos, Jina Suh, Johan Verwey, Mo Wang, John Wernsing:
Machine Teaching: A New Paradigm for Building Machine Learning Systems. CoRR abs/1707.06742 (2017) - 2016
- [i21]Camille Jandot, Patrice Y. Simard, Max Chickering, David Grangier, Jina Suh:
Interactive Semantic Featuring for Text Classification. CoRR abs/1606.07545 (2016) - 2015
- [c42]Saleema Amershi, Max Chickering, Steven Mark Drucker, Bongshin Lee, Patrice Y. Simard, Jina Suh:
ModelTracker: Redesigning Performance Analysis Tools for Machine Learning. CHI 2015: 337-346 - [c41]David Maxwell Chickering, Christopher Meek:
Selective Greedy Equivalence Search: Finding Optimal Bayesian Networks Using a Polynomial Number of Score Evaluations. UAI 2015: 211-219 - [i20]David Maxwell Chickering, Christopher Meek:
Selective Greedy Equivalence Search: Finding Optimal Bayesian Networks Using a Polynomial Number of Score Evaluations. CoRR abs/1506.02113 (2015) - 2014
- [c40]Hossein Azari Soufiani, David Maxwell Chickering, Denis Xavier Charles, David C. Parkes:
Approximating the shapley value via multi-issue decompositions. AAMAS 2014: 1209-1216 - [i19]Patrice Y. Simard, David Maxwell Chickering, Aparna Lakshmiratan, Denis Xavier Charles, Léon Bottou, Carlos Garcia Jurado Suarez, David Grangier, Saleema Amershi, Johan Verwey, Jina Suh:
ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems. CoRR abs/1409.4814 (2014) - 2013
- [j17]Léon Bottou, Jonas Peters, Joaquin Quiñonero Candela, Denis Xavier Charles, Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Y. Simard, Ed Snelson:
Counterfactual reasoning and learning systems: the example of computational advertising. J. Mach. Learn. Res. 14(1): 3207-3260 (2013) - [c39]Denis Xavier Charles, Deeparnab Chakrabarty, Max Chickering, Nikhil R. Devanur, Lei Wang:
Budget smoothing for internet ad auctions: a game theoretic approach. EC 2013: 163-180 - [i18]David Maxwell Chickering, Christopher Meek:
Finding Optimal Bayesian Networks. CoRR abs/1301.0561 (2013) - [i17]Eric Horvitz, Yongshao Ruan, Carla P. Gomes, Henry A. Kautz, Bart Selman, David Maxwell Chickering:
A Bayesian Approach to Tackling Hard Computational Problems. CoRR abs/1301.2279 (2013) - [i16]Andrew Zimdars, David Maxwell Chickering, Christopher Meek:
Using Temporal Data for Making Recommendations. CoRR abs/1301.2320 (2013) - [i15]David Maxwell Chickering, David Heckerman:
A Decision Theoretic Approach to Targeted Advertising. CoRR abs/1301.3842 (2013) - [i14]David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie:
Dependency Networks for Collaborative Filtering and Data Visualization. CoRR abs/1301.3862 (2013) - [i13]David Maxwell Chickering, David Heckerman:
Fast Learning from Sparse Data. CoRR abs/1301.6685 (2013) - [i12]Bo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman:
Learning Mixtures of DAG Models. CoRR abs/1301.7415 (2013) - [i11]David Maxwell Chickering, David Heckerman, Christopher Meek:
A Bayesian Approach to Learning Bayesian Networks with Local Structure. CoRR abs/1302.1528 (2013) - [i10]David Maxwell Chickering:
Learning Equivalence Classes of Bayesian Networks Structures. CoRR abs/1302.3566 (2013) - [i9]David Maxwell Chickering, David Heckerman:
Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network. CoRR abs/1302.3567 (2013) - [i8]David Maxwell Chickering:
A Transformational Characterization of Equivalent Bayesian Network Structures. CoRR abs/1302.4938 (2013) - [i7]David Heckerman, Dan Geiger, David Maxwell Chickering:
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. CoRR abs/1302.6815 (2013) - 2012
- [i6]Bo Thiesson, David Maxwell Chickering, David Heckerman, Christopher Meek:
ARMA Time-Series Modeling with Graphical Models. CoRR abs/1207.4162 (2012) - [i5]Max Chickering, Joseph Y. Halpern:
Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (2004). CoRR abs/1208.5161 (2012) - [i4]Léon Bottou, Jonas Peters, Joaquin Quiñonero Candela, Denis Xavier Charles, Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Y. Simard, Ed Snelson:
Counterfactual Reasoning and Learning Systems. CoRR abs/1209.2355 (2012) - [i3]David Maxwell Chickering, Christopher Meek, David Heckerman:
Large-Sample Learning of Bayesian Networks is NP-Hard. CoRR abs/1212.2468 (2012) - [i2]Christopher Meek, David Maxwell Chickering:
Practically Perfect. CoRR abs/1212.2503 (2012) - 2011
- [i1]Greg Linden, Christopher Meek, Max Chickering:
The Pollution Effect: Optimizing Keyword Auctions by Favoring Relevant Advertising. CoRR abs/1109.6263 (2011) - 2010
- [c38]Tim Paek, Michael Gamon, Scott Counts, David Maxwell Chickering, Aman Dhesi:
Predicting the Importance of Newsfeed Posts and Social Network Friends. AAAI 2010: 1419-1424 - [c37]Sven Seuken, Denis Xavier Charles, Max Chickering, Sidd Puri:
Market design & analysis for a P2P backup system. EC 2010: 97-108 - [c36]Denis Xavier Charles, Max Chickering, Nikhil R. Devanur, Kamal Jain, Manan Sanghi:
Fast algorithms for finding matchings in lopsided bipartite graphs with applications to display ads. EC 2010: 121-128
2000 – 2009
- 2009
- [c35]Sven Seuken, Denis Xavier Charles, Max Chickering, Sidd Puri:
Market Design for a P2P Backup System. AMMA 2009: 55-57 - [c34]Edith Law, Anton Mityagin, David Maxwell Chickering:
Intentions: a game for classifying search query intent. CHI Extended Abstracts 2009: 3805-3810 - [c33]Paul N. Bennett, David Maxwell Chickering, Anton Mityagin:
Picture this: preferences for image search. KDD Workshop on Human Computation 2009: 25-26 - [c32]Paul N. Bennett, David Maxwell Chickering, Anton Mityagin:
Learning consensus opinion: mining data from a labeling game. WWW 2009: 121-130 - [e2]Paul N. Bennett, Raman Chandrasekar, Max Chickering, Panagiotis G. Ipeirotis, Edith Law, Anton Mityagin, Foster J. Provost, Luis von Ahn:
Proceedings of the ACM SIGKDD Workshop on Human Computation, Paris, France, June 28, 2009. ACM 2009, ISBN 978-1-60558-672-4 [contents] - 2008
- [c31]Yagil Engel, David Maxwell Chickering:
Incorporating user utility into sponsored-search auctions. AAMAS (3) 2008: 1565-1568 - [c30]Ben Carterette, Paul N. Bennett, David Maxwell Chickering, Susan T. Dumais:
Here or There. ECIR 2008: 16-27 - [c29]Guy Shani
, David Maxwell Chickering, Christopher Meek:
Mining recommendations from the web. RecSys 2008: 35-42 - [c28]Tim Paek, Sudeep Gandhe, Max Chickering:
Rapidly Deploying Grammar-Based Speech Applications with Active Learning and Back-off Grammars. SIGDIAL Workshop 2008: 64-67 - 2007
- [j16]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) - [j15]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) - [c27]Hila Becker, Christopher Meek, David Maxwell Chickering:
Modeling Contextual Factors of Click Rates. AAAI 2007: 1310-1315 - 2006
- [j14]David Maxwell Chickering, Christopher Meek:
On the incompatibility of faithfulness and monotone DAG faithfulness. Artif. Intell. 170(8-9): 653-666 (2006) - [j13]Tim Paek, David Maxwell Chickering:
Evaluating the Markov assumption in Markov Decision Processes for spoken dialogue management. Lang. Resour. Evaluation 40(1): 47-66 (2006) - [c26]Kumar Chellapilla, David Maxwell Chickering:
Improving Cloaking Detection using Search Query Popularity and Monetizability. AIRWeb 2006: 17-23 - 2005
- [c25]Tim Paek, David Maxwell Chickering:
The Markov Assumption in Spoken Dialogue Management. SIGDIAL Workshop 2005: 35-44 - 2004
- [j12]David Maxwell Chickering, David Heckerman, Christopher Meek:
Large-Sample Learning of Bayesian Networks is NP-Hard. J. Mach. Learn. Res. 5: 1287-1330 (2004) - [c24]Bo Thiesson, David Maxwell Chickering, David Heckerman, Christopher Meek:
ARMA Time-Series Modeling with Graphical Models. UAI 2004: 552-560 - [e1]David Maxwell Chickering, Joseph Y. Halpern:
UAI '04, Proceedings of the 20th Conference in Uncertainty in Artificial Intelligence, Banff, Canada, July 7-11, 2004. AUAI Press 2004, ISBN 0-9749039-0-6 [contents] - 2003
- [j11]David Maxwell Chickering, David Heckerman:
Targeted Advertising on the Web with Inventory Management. Interfaces 33(5): 71-77 (2003) - [c23]Geoff Hulten, David Maxwell Chickering, David Heckerman:
Learning Bayesian Networks From Dependency Networks: A Preliminary Study. AISTATS 2003: 141-148 - [c22]David Maxwell Chickering, Christopher Meek, David Heckerman:
Large-Sample Learning of Bayesian Networks is NP-Hard. UAI 2003: 124-133 - [c21]Christopher Meek, David Maxwell Chickering:
Practically Perfect. UAI 2003: 411-416 - 2002
- [j10]David Maxwell Chickering:
Learning Equivalence Classes of Bayesian-Network Structures. J. Mach. Learn. Res. 2: 445-498 (2002) - [j9]David Maxwell Chickering:
Optimal Structure Identification With Greedy Search. J. Mach. Learn. Res. 3: 507-554 (2002) - [c20]Christopher Meek, David Maxwell Chickering, David Heckerman:
Autoregressive Tree Models for Time-Series Analysis. SDM 2002: 229-244 - [c19]David Maxwell Chickering, Christopher Meek:
Finding Optimal Bayesian Networks. UAI 2002: 94-102 - 2001
- [j8]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). Electron. Notes Discret. Math. 9: 376-391 (2001) - [c18]David Maxwell Chickering, Christopher Meek, Robert Rounthwaite:
Efficient Determination of Dynamic Split Points in a Decision Tree. ICDM 2001: 91-98 - [c17]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 - [c16]Andrew Zimdars, David Maxwell Chickering, Christopher Meek:
Using Temporal Data for Making Recommendations. UAI 2001: 580-588 - 2000
- [j7]David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie:
Dependency Networks for Inference, Collaborative Filtering, and Data Visualization. J. Mach. Learn. Res. 1: 49-75 (2000) - [j6]David Maxwell Chickering, David Heckerman:
A comparison of scientific and engineering criteria for Bayesian model selection. Stat. Comput. 10(1): 55-62 (2000) - [c15]David Maxwell Chickering, David Heckerman:
Targeted advertising with inventory management. EC 2000: 145-149 - [c14]David Maxwell Chickering, David Heckerman:
A Decision Theoretic Approach to Targeted Advertising. UAI 2000: 82-88 - [c13]David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie:
Dependency Networks for Collaborative Filtering and Data Visualization. UAI 2000: 264-273
1990 – 1999
- 1999
- [c12]David Maxwell Chickering, David Heckerman:
Fast Learning from Sparse Data. UAI 1999: 109-115 - 1998
- [c11]Bo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman:
Learning Mixtures of DAG Models. UAI 1998: 504-513 - 1997
- [j5]David Maxwell Chickering, David Heckerman:
Efficient Approximations for the Marginal Likelihood of Bayesian Networks with Hidden Variables. Mach. Learn. 29(2-3): 181-212 (1997) - [c10]David Heckerman, David Maxwell Chickering:
A Comparison of Scientific and Engineering Criteria for Bayesian Model Selection. AISTATS 1997: 275-282 - [c9]David Maxwell Chickering, David Heckerman, Christopher Meek:
A Bayesian Approach to Learning Bayesian Networks with Local Structure. UAI 1997: 80-89 - 1996
- [j4]Richard E. Korf, David Maxwell Chickering:
Best-First Minimax Search. Artif. Intell. 84(1-2): 299-337 (1996) - [j3]Richard E. Korf, David Maxwell Chickering:
Best-First Minimax Search. J. Int. Comput. Games Assoc. 19(3): 187 (1996) - [c8]David Maxwell Chickering, Judea Pearl:
A Clinician's Tool for Analyzing Non-Compliance. AAAI/IAAI, Vol. 2 1996: 1269-1276 - [c7]David Maxwell Chickering:
Learning Equivalence Classes of Bayesian Network Structures. UAI 1996: 150-157 - [c6]David Maxwell Chickering, David Heckerman:
Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network. UAI 1996: 158-168 - 1995
- [j2]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) - [j1]David Heckerman, Dan Geiger, David Maxwell Chickering:
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. Mach. Learn. 20(3): 197-243 (1995) - [c5]David Maxwell Chickering:
Learning Bayesian Networks is NP-Complete. AISTATS 1995: 121-130 - [c4]David Maxwell Chickering:
A Transformational Characterization of Equivalent Bayesian Network Structures. UAI 1995: 87-98 - 1994
- [c3]Richard E. Korf, David Maxwell Chickering:
Best-First Minimax Search: Othello Results. AAAI 1994: 1365-1370 - [c2]David Heckerman, Dan Geiger, David Maxwell Chickering:
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. KDD Workshop 1994: 85-96 - [c1]David Heckerman, Dan Geiger, David Maxwell Chickering:
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. UAI 1994: 293-301
Coauthor Index
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