ML Lab - Papers

2018

Collective Classification of Social Network Spam. Jonathan Brophy and Daniel Lowd. 2017 AAAI Workshop on Artificial Intelligence and Cyber-Security (AICS), 2017. San Francisco, CA: AAAI.

A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets. Javid Ebrahimi, Dejing Dou, and Daniel Lowd. Proceedings of the 26th International Conference on Computational Linguistics (COLING 2016) (pp. 2656-2665), 2016.
Weakly Supervised Tweet Stance Classification by Relational Bootstrapping. Javid Ebrahimi, Dejing Dou, and Daniel Lowd. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2016) (pp. 1012-1017) (short paper), 2016.
Ontology-based Deep Restricted Boltzmann Machine. Hao Wang, Dejing Dou, and Daniel Lowd. Proceedings of the 27th International Conference on Database and Expert Systems Applications (DEXA 2016) (pp. 431-445), 2016. Porto, Portugal.
Discriminative Structure Learning of Arithmetic Circuits. Amirmohammad Rooshenas and Daniel Lowd. Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), 2016. Cadiz, Spain. (Supplementary material)
A Probabilistic Approach to Knowledge Translation. Shangpu Jiang, Daniel Lowd, and Dejing Dou. Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI), 2016. Phoenix, AZ.

Ontology Matching with Knowledge Rules. Shangpu Jiang, Daniel Lowd, and Dejing Dou. Proceedings of the 26th International Conference on Database and Expert Systems Applications (DEXA), 2015. Valencia, Spain. (Best Paper Award)
Automated Attacks on Compression-Based Classifiers. Igor Burago and Daniel Lowd. 2015 ACM Workshop on Artificial Intelligence and Security (AISec), 2015. Denver, Colorado: ACM.
A Probabilistic Approach to Knowledge Translation. Shangpu Jiang, Daniel Lowd, and Dejing Dou, Fifth International Workshop on Statistical Relational AI (StaR AI 2015), 2015.
Ontology Matching with Knowledge Rules. Shangpu Jiang, Daniel Lowd, and Dejing Dou, Fifth International Workshop on Statistical Relational AI (StaR AI 2015), 2015.

Inferring Coarse Views of Connectivity in Very Large Graphs. Reza Motamedi, Reza Rejaie, Walter Willinger, Daniel Lowd, and Roberto Gonzalez. Proceedings of the ACM Conference on Online Social Networks (COSN'14), 2014. Dublin, Ireland.
On Robustness and Regularization of Structural Support Vector Machines. MohamadAli Torkamani and Daniel Lowd. Proceedings of the 31st International Conference on Machine Learning (ICML), 2014. Beijing, China. (Supplemental proofs)
Learning Sum-Product Networks with Direct and Indirect Interactions. Amirmohammad Rooshenas and Daniel Lowd. Proceedings of the 31st International Conference on Machine Learning (ICML), 2014. Beijing, China.
Leveraging USB to Establish Host Identity Using Commodity Devices. Adam Bates, Ryan Leonard, Hannah Pruse, Daniel Lowd, and Kevin Butler. Proceedings of the 21st ISOC Network and Distributed System Security Symposium (NDSS), 2014. San Diego, CA.
Towards Adversarial Reasoning in Statistical Relational Domains. Daniel Lowd, Brenton Lessley, and Mino De Raj. AAAI-14 Workshop on Statistical Relational AI (Star AI 2014), 2014.

Learning Markov Networks with Arithmetic Circuits. Daniel Lowd and Amirmohammad Rooshenas. Proceedings of the 16th International Conference on Artificial Intelligence and Statistics (AISTATS), 2013. Scottsdale, AZ, USA.
Convex Adversarial Collective Classification. MohamadAli Torkamani and Daniel Lowd. Proceedings of the 30th International Conference on Machine Learning (ICML), 2013. Atlanta, GA, USA.
On the Hardness of Evading Combinations of Linear Classifiers. David Stevens and Daniel Lowd. 2013 ACM Workshop on Artificial Intelligence and Security (AISec), 2013. Berlin, Germany: ACM.

Learning to Refine an Automatically Extracted Knowledge Base using Markov Logic. Shangpu Jiang, Daniel Lowd, and Dejing Dou. Proceedings of the IEEE International Conference on Data Mining (ICDM), 2012. Brussels, Belgium. (Workshop version; Data)
Closed-Form Learning of Markov Networks from Dependency Networks. Daniel Lowd. Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI-12), 2012. Catalina Island, CA. (Spotlight; Poster)

Mean Field Inference in Dependency Networks: An Empirical Study. Daniel Lowd and Arash Shamaei. Proceedings of the 25th Conference on Artificial Intelligence (AAAI-11), 2011. San Francisco, CA. (Slides; Online appendix)