Daniel Lowd

	2011
16		Daniel Lowd, Arash Shamaei: Mean Field Inference in Dependency Networks: An Empirical Study. AAAI 2011
	2010
15		Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik: Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. ECML/PKDD (2) 2010: 434-450
14		Daniel Lowd, Jesse Davis: Learning Markov Network Structure with Decision Trees. ICDM 2010: 334-343
13		Daniel Lowd, Pedro Domingos: Approximate Inference by Compilation to Arithmetic Circuits. NIPS 2010: 1477-1485
12		Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik: Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. Statistical Relational Artificial Intelligence 2010
	2009
11		Pedro Domingos, Daniel Lowd: Markov Logic: An Interface Layer for Artificial Intelligence Morgan & Claypool Publishers 2009
10		Daniel Lowd, Nicholas Kushmerick: Using salience to segment desktop activity into projects. IUI 2009: 463-468
	2008
9		Pedro Domingos, Stanley Kok, Daniel Lowd, Hoifung Poon, Matthew Richardson, Parag Singla: Markov Logic. Probabilistic Inductive Logic Programming 2008: 92-117
8		Pedro Domingos, Stanley Kok, Daniel Lowd, Hoifung Poon, Matthew Richardson, Parag Singla, Marc Sumner, Jue Wang: Markov Logic: A Unifying Language for Structural and Statistical Pattern Recognition. SSPR/SPR 2008: 3
7		Daniel Lowd, Pedro Domingos: Learning Arithmetic Circuits. UAI 2008: 383-392
6		Pedro Domingos, Daniel Lowd, Stanley Kok, Hoifung Poon, Matthew Richardson, Parag Singla: Just Add Weights: Markov Logic for the Semantic Web. URSW (LNCS Vol.) 2008: 1-25
	2007
5		Daniel Lowd, Pedro Domingos: Recursive Random Fields. IJCAI 2007: 950-955
4		Daniel Lowd, Pedro Domingos: Efficient Weight Learning for Markov Logic Networks. PKDD 2007: 200-211
	2005
3		Daniel Lowd, Christopher Meek: Good Word Attacks on Statistical Spam Filters. CEAS 2005
2		Daniel Lowd, Pedro Domingos: Naive Bayes models for probability estimation. ICML 2005: 529-536
1		Daniel Lowd, Christopher Meek: Adversarial learning. KDD 2005: 641-647

Coauthor Index

1	Jesse Davis	[14]
2	Pedro Domingos	[2] [4] [5] [6] [7] [8] [9] [11] [13]
3	Kristian Kersting	[12] [15]
4	Tushar Khot	[12] [15]
5	Stanley Kok	[6] [8] [9]
6	Nicholas Kushmerick	[10]
7	Christopher Meek	[1] [3]
8	Sriraam Natarajan	[12] [15]
9	Hoifung Poon	[6] [8] [9]
10	Matthew Richardson	[6] [8] [9]
11	Arash Shamaei	[16]
12	Jude W. Shavlik	[12] [15]
13	Parag Singla	[6] [8] [9]
14	Marc Sumner	[8]
15	Prasad Tadepalli	[12] [15]
16	Jue Wang	[8]

Colors in the list of coauthors

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