Good Word Attacks on Statistical Spam Filters. - Daniel Lowd; Christopher Meek (CEAS, 2005)

Naive Bayes models for probability estimation. - Daniel Lowd; Pedro M. Domingos (ICML, 2005)

Adversarial learning. - Daniel Lowd; Christopher Meek (KDD, 2005)

Recursive Random Fields. - Daniel Lowd; Pedro M. Domingos (IJCAI, 2007)

Efficient Weight Learning for Markov Logic Networks. - Daniel Lowd; Pedro M. Domingos (PKDD, 2007)

Markov Logic. - Pedro M. Domingos; Stanley Kok; Daniel Lowd; Hoifung Poon; Matthew Richardson; Parag Singla (Probabilistic Inductive Logic Programming, 2008)

Just Add Weights: Markov Logic for the Semantic Web. - Pedro M. Domingos; Daniel Lowd; Stanley Kok; Hoifung Poon; Matthew Richardson; Parag Singla (URSW (LNCS Vol.), 2008)

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 (SSPR/SPR, 2008)

Learning Arithmetic Circuits. - Daniel Lowd; Pedro M. Domingos (UAI, 2008)

Using salience to segment desktop activity into projects. - Daniel Lowd; Nicholas Kushmerick (IUI, 2009)

Markov Logic: An Interface Layer for Artificial Intelligence - Pedro M. Domingos; Daniel Lowd (Markov Logic, 2009)

Markov Logic: A Language and Algorithms for Link Mining. - Pedro M. Domingos; Daniel Lowd; Stanley Kok; Aniruddh Nath; Hoifung Poon; Matthew Richardson; Parag Singla (Link Mining, 2010)

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 (StarAI@AAAI, 2010)

Learning Markov Network Structure with Decision Trees. - Daniel Lowd; Jesse Davis (ICDM, 2010)

Approximate Inference by Compilation to Arithmetic Circuits. - Daniel Lowd; Pedro M. Domingos (NIPS, 2010)

Mean Field Inference in Dependency Networks: An Empirical Study. - Daniel Lowd; Arash Shamaei (AAAI, 2011)

Learning to Refine an Automatically Extracted Knowledge Base Using Markov Logic. - Shangpu Jiang; Daniel Lowd; Dejing Dou (ICDM, 2012)

Using Markov Logic to Refine an Automatically Extracted Knowledge Base. - Shangpu Jiang; Daniel Lowd; Dejing Dou (StarAI@UAI, 2012)

Closed-Form Learning of Markov Networks from Dependency Networks. - Daniel Lowd (UAI, 2012)

Learning Tractable Graphical Models Using Mixture of Arithmetic Circuits. - Amirmohammad Rooshenas; Daniel Lowd (AAAI (Late-Breaking Developments), 2013)

Learning Markov Networks With Arithmetic Circuits. - Daniel Lowd; Amirmohammad Rooshenas (AISTATS, 2013)

On the hardness of evading combinations of linear classifiers. - David Stevens; Daniel Lowd (AISec, 2013)

Convex Adversarial Collective Classification. - MohamadAli Torkamani; Daniel Lowd (ICML (1), 2013)

Towards Adversarial Reasoning in Statistical Relational Domains. - Daniel Lowd; Brenton Lessley; Mino De Raj (StarAI@AAAI, 2014)

Inferring coarse views of connectivity in very large graphs. - Reza Motamedi; Reza Rejaie; Walter Willinger; Daniel Lowd; Roberto Gonzalez (COSN, 2014)

Learning Sum-Product Networks with Direct and Indirect Variable Interactions. - Amirmohammad Rooshenas; Daniel Lowd (ICML, 2014)

On Robustness and Regularization of Structural Support Vector Machines. - MohamadAli Torkamani; Daniel Lowd (ICML, 2014)

Leveraging USB to Establish Host Identity Using Commodity Devices. - Adam Bates 001; Ryan Leonard; Hannah Pruse; Daniel Lowd; Kevin R. B. Butler (NDSS, 2014)

Improving Markov network structure learning using decision trees. - Daniel Lowd; Jesse Davis (J. Mach. Learn. Res., 2014)

Automated Attacks on Compression-Based Classifiers. - Igor Burago; Daniel Lowd (AISec@CCS, 2015)

Ontology Matching with Knowledge Rules. - Shangpu Jiang; Daniel Lowd; Dejing Dou (DEXA (1), 2015)

The Libra toolkit for probabilistic models. - Daniel Lowd; Amirmohammad Rooshenas (J. Mach. Learn. Res., 2015)

A Probabilistic Approach to Knowledge Translation. - Shangpu Jiang; Daniel Lowd; Dejing Dou (AAAI, 2016)

Discriminative Structure Learning of Arithmetic Circuits. - Amirmohammad Rooshenas; Daniel Lowd (AAAI, 2016)

A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets. - Javid Ebrahimi; Dejing Dou; Daniel Lowd (COLING, 2016)

Ontology-Based Deep Restricted Boltzmann Machine. - Hao Wang 064; Dejing Dou; Daniel Lowd (DEXA (1), 2016)

Weakly Supervised Tweet Stance Classification by Relational Bootstrapping. - Javid Ebrahimi; Dejing Dou; Daniel Lowd (EMNLP, 2016)

Unifying Logical and Statistical AI. - Pedro M. Domingos; Daniel Lowd; Stanley Kok; Aniruddh Nath; Hoifung Poon; Matthew Richardson; Parag Singla (LICS, 2016)

Ontology Matching with Knowledge Rules. - Shangpu Jiang; Daniel Lowd; Sabin Kafle; Dejing Dou (Trans. Large Scale Data Knowl. Centered Syst., 2016)

Collective Classification of Social Network Spam. - Jonathan Brophy; Daniel Lowd (AAAI Workshops, 2017)

A Temporal Attentional Model for Rumor Stance Classification. - Amir Pouran Ben Veyseh; Javid Ebrahimi; Dejing Dou; Daniel Lowd (CIKM, 2017)

Neural-Symbolic Learning and Reasoning: A Survey and Interpretation. - Tarek R. Besold; Artur S. d'Avila Garcez; Sebastian Bader 001; Howard Bowman; Pedro M. Domingos; Pascal Hitzler; Kai-Uwe Kühnberger; Luís C. Lamb; Daniel Lowd; Priscila Machado Vieira Lima; Leo de Penning; Gadi Pinkas; et al. (CoRR, 2017)

HotFlip: White-Box Adversarial Examples for NLP. - Javid Ebrahimi; Anyi Rao; Daniel Lowd; Dejing Dou (CoRR, 2017)

HotFlip: White-Box Adversarial Examples for Text Classification. - Javid Ebrahimi; Anyi Rao; Daniel Lowd; Dejing Dou (ACL (2), 2018)

On Adversarial Examples for Character-Level Neural Machine Translation. - Javid Ebrahimi; Daniel Lowd; Dejing Dou (COLING, 2018)

Unifying logical and statistical AI with Markov logic. - Pedro M. Domingos; Daniel Lowd (Commun. ACM, 2019)

Learning from Positive and Unlabeled Data with Arbitrary Positive Shift. - Zayd Hammoudeh; Daniel Lowd (NeurIPS, 2020)

On the Practicality of Learning Models for Network Telemetry. - Soheil Jamshidi; Zayd Hammoudeh; Ramakrishnan Durairajan; Daniel Lowd; Reza Rejaie; Walter Willinger (TMA, 2020)

EGGS: A Flexible Approach to Relational Modeling of Social Network Spam. - Jonathan Brophy; Daniel Lowd (CoRR, 2020)

TREX: Tree-Ensemble Representer-Point Explanations. - Jonathan Brophy; Daniel Lowd (CoRR, 2020)

DART: Data Addition and Removal Trees. - Jonathan Brophy; Daniel Lowd (CoRR, 2020)

What Models Know About Their Attackers: Deriving Attacker Information From Latent Representations. - Zhouhang Xie; Jonathan Brophy; Adam Noack; Wencong You; Kalyani Asthana; Carter Perkins; Sabrina Reis; Zayd Hammoudeh; Daniel Lowd; Sameer Singh 001 (BlackboxNLP@EMNLP, 2021)

Machine Unlearning for Random Forests. - Jonathan Brophy; Daniel Lowd (ICML, 2021)

Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation. - Zayd Hammoudeh; Daniel Lowd (CCS, 2022)

Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees. - Jonathan Brophy; Daniel Lowd (NeurIPS, 2022)

Identifying Adversarial Attacks on Text Classifiers. - Zhouhang Xie; Jonathan Brophy; Adam Noack; Wencong You; Kalyani Asthana; Carter Perkins; Sabrina Reis; Sameer Singh 001; Daniel Lowd (CoRR, 2022)

Reducing Certified Regression to Certified Classification. - Zayd Hammoudeh; Daniel Lowd (CoRR, 2022)

TCAB: A Large-Scale Text Classification Attack Benchmark. - Kalyani Asthana; Zhouhang Xie; Wencong You; Adam Noack; Jonathan Brophy; Sameer Singh 001; Daniel Lowd (CoRR, 2022)

Large Language Models Are Better Adversaries: Exploring Generative Clean-Label Backdoor Attacks Against Text Classifiers. - Wencong You; Zayd Hammoudeh; Daniel Lowd (EMNLP (Findings), 2023)

Reducing Certified Regression to Certified Classification for General Poisoning Attacks. - Zayd Hammoudeh; Daniel Lowd (SaTML, 2023)

Feature Partition Aggregation: A Fast Certified Defense Against a Union of Sparse Adversarial Attacks. - Zayd Hammoudeh; Daniel Lowd (CoRR, 2023)

Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees. - Jonathan Brophy; Zayd Hammoudeh; Daniel Lowd (J. Mach. Learn. Res., 2023)

Provable Robustness against a Union of L_0 Adversarial Attacks. - Zayd Hammoudeh; Daniel Lowd (AAAI, 2024)

MaPPing Your Model: Assessing the Impact of Adversarial Attacks on LLM-based Programming Assistants. - John Heibel; Daniel Lowd (CoRR, 2024)

Training data influence analysis and estimation: a survey. - Zayd Hammoudeh; Daniel Lowd (Mach. Learn., 2024)

On the Practicality of Differential Privacy for Knowledge Tracing. - Anika Kabir; Chandan Tankala; Daniel Lowd (EDM, 2025)

The Ultimate Cookbook for Invisible Poison: Crafting Subtle Clean-Label Text Backdoors with Style Attributes. - Wencong You; Daniel Lowd (SaTML, 2025)