| 2025 | EDM | On the Practicality of Differential Privacy for Knowledge Tracing. | Anika Kabir, Chandan Tankala, Daniel Lowd |
| 2024 | AAAI | Provable Robustness against a Union of L_0 Adversarial Attacks. | Zayd Hammoudeh, Daniel Lowd |
| 2023 | EMNLP | Large Language Models Are Better Adversaries: Exploring Generative Clean-Label Backdoor Attacks Against Text Classifiers. | Wencong You, Zayd Hammoudeh, Daniel Lowd |
| 2022 | CCS | Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation. | Zayd Hammoudeh, Daniel Lowd |
| 2021 | ICML | Machine Unlearning for Random Forests. | Jonathan Brophy, Daniel Lowd |
| 2018 | ACL | HotFlip: White-Box Adversarial Examples for Text Classification. | Javid Ebrahimi, Anyi Rao, Daniel Lowd, Dejing Dou |
| 2018 | COLING | On Adversarial Examples for Character-Level Neural Machine Translation. | Javid Ebrahimi, Daniel Lowd, Dejing Dou |
| 2017 | AAAI | Collective Classification of Social Network Spam. | Jonathan Brophy, Daniel Lowd |
| 2017 | CIKM | A Temporal Attentional Model for Rumor Stance Classification. | Amir Pouran Ben Veyseh, Javid Ebrahimi, Dejing Dou, Daniel Lowd |
| 2016 | AAAI | A Probabilistic Approach to Knowledge Translation. | Shangpu Jiang, Daniel Lowd, Dejing Dou |
| 2016 | AAAI | Discriminative Structure Learning of Arithmetic Circuits. | Amirmohammad Rooshenas, Daniel Lowd |
| 2016 | AISTATS | Discriminative Structure Learning of Arithmetic Circuits. | Amirmohammad Rooshenas, Daniel Lowd |
| 2016 | COLING | A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets. | Javid Ebrahimi, Dejing Dou, Daniel Lowd |
| 2016 | DEXA | Ontology-Based Deep Restricted Boltzmann Machine. | Hao Wang, Dejing Dou, Daniel Lowd |
| 2016 | EMNLP | Weakly Supervised Tweet Stance Classification by Relational Bootstrapping. | Javid Ebrahimi, Dejing Dou, Daniel Lowd |
| 2016 | LICS | Unifying Logical and Statistical AI. | Pedro M. Domingos, Daniel Lowd, Stanley Kok, Aniruddh Nath, Hoifung Poon, Matthew Richardson, Parag Singla |
| 2015 | CCS | Automated Attacks on Compression-Based Classifiers. | Igor Burago, Daniel Lowd |
| 2015 | DEXA | Ontology Matching with Knowledge Rules. | Shangpu Jiang, Daniel Lowd, Dejing Dou |
| 2014 | AAAI | Towards Adversarial Reasoning in Statistical Relational Domains. | Daniel Lowd, Brenton Lessley, Mino De Raj |
| 2014 | ICML | Learning Sum-Product Networks with Direct and Indirect Variable Interactions. | Amirmohammad Rooshenas, Daniel Lowd |
| 2014 | ICML | On Robustness and Regularization of Structural Support Vector Machines. | MohamadAli Torkamani, Daniel Lowd |
| 2014 | NDSS | Leveraging USB to Establish Host Identity Using Commodity Devices. | Adam Bates, Ryan Leonard, Hannah Pruse, Daniel Lowd, Kevin R. B. Butler |
| 2013 | AAAI | Learning Tractable Graphical Models Using Mixture of Arithmetic Circuits. | Amirmohammad Rooshenas, Daniel Lowd |
| 2013 | AISTATS | Learning Markov Networks With Arithmetic Circuits. | Daniel Lowd, Amirmohammad Rooshenas |
| 2013 | CCS | On the hardness of evading combinations of linear classifiers. | David Stevens, Daniel Lowd |
| 2013 | ICML | Convex Adversarial Collective Classification. | MohamadAli Torkamani, Daniel Lowd |
| 2012 | ICDM | Learning to Refine an Automatically Extracted Knowledge Base Using Markov Logic. | Shangpu Jiang, Daniel Lowd, Dejing Dou |
| 2012 | UAI | Closed-Form Learning of Markov Networks from Dependency Networks. | Daniel Lowd |
| 2011 | AAAI | Mean Field Inference in Dependency Networks: An Empirical Study. | Daniel Lowd, Arash Shamaei |
| 2010 | AAAI | Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. | Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik |
| 2010 | ICDM | Learning Markov Network Structure with Decision Trees. | Daniel Lowd, Jesse Davis |
| 2009 | IUI | Using salience to segment desktop activity into projects. | Daniel Lowd, Nicholas Kushmerick |
| 2008 | UAI | Learning Arithmetic Circuits. | Daniel Lowd, Pedro M. Domingos |
| 2008 | SSPR | Markov Logic: A Unifying Language for Structural and Statistical Pattern Recognition. | Pedro M. Domingos, Stanley Kok, Daniel Lowd, Hoifung Poon, Matthew Richardson, Parag Singla, Marc Sumner, Jue Wang |
| 2007 | IJCAI | Recursive Random Fields. | Daniel Lowd, Pedro M. Domingos |
| 2005 | ICML | Naive Bayes models for probability estimation. | Daniel Lowd, Pedro M. Domingos |
| 2005 | KDD | Adversarial learning. | Daniel Lowd, Christopher Meek |