Daniel Lowd

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 41

Top Topics

Restricted Boltzmann Machine

Boosted Decision Trees

Structure Learning

Top Venues

J. Mach. Learn. Res.

Publications

Zayd Hammoudeh, Daniel Lowd
Training data influence analysis and estimation: a survey. Mach. Learn. 113 (5) (2024)
John Heibel, Daniel Lowd
MaPPing Your Model: Assessing the Impact of Adversarial Attacks on LLM-based Programming Assistants. CoRR (2024)
Zayd Hammoudeh, Daniel Lowd
Provable Robustness against a Union of L_0 Adversarial Attacks. AAAI (2024)
Jonathan Brophy, Zayd Hammoudeh, Daniel Lowd
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees. J. Mach. Learn. Res. 24 (2023)
Wencong You, Zayd Hammoudeh, Daniel Lowd
Large Language Models Are Better Adversaries: Exploring Generative Clean-Label Backdoor Attacks Against Text Classifiers. CoRR (2023)
Zayd Hammoudeh, Daniel Lowd
Feature Partition Aggregation: A Fast Certified Defense Against a Union of Sparse Adversarial Attacks. CoRR (2023)
Wencong You, Zayd Hammoudeh, Daniel Lowd
Large Language Models Are Better Adversaries: Exploring Generative Clean-Label Backdoor Attacks Against Text Classifiers. EMNLP (Findings) (2023)
Zayd Hammoudeh, Daniel Lowd
Reducing Certified Regression to Certified Classification for General Poisoning Attacks. SaTML (2023)
Zhouhang Xie, Jonathan Brophy, Adam Noack, Wencong You, Kalyani Asthana, Carter Perkins, Sabrina Reis, Sameer Singh, Daniel Lowd
Identifying Adversarial Attacks on Text Classifiers. CoRR (2022)
Jonathan Brophy, Daniel Lowd
Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees. CoRR (2022)
Zayd Hammoudeh, Daniel Lowd
Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation. CoRR (2022)
Jonathan Brophy, Daniel Lowd
Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees. NeurIPS (2022)
Zayd Hammoudeh, Daniel Lowd
Training Data Influence Analysis and Estimation: A Survey. CoRR (2022)
Zayd Hammoudeh, Daniel Lowd
Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation. CCS (2022)
Kalyani Asthana, Zhouhang Xie, Wencong You, Adam Noack, Jonathan Brophy, Sameer Singh, Daniel Lowd
TCAB: A Large-Scale Text Classification Attack Benchmark. CoRR (2022)
Zayd Hammoudeh, Daniel Lowd
Reducing Certified Regression to Certified Classification. CoRR (2022)
Jonathan Brophy, Zayd Hammoudeh, Daniel Lowd
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees. CoRR (2022)
Zhouhang Xie, Jonathan Brophy, Adam Noack, Wencong You, Kalyani Asthana, Carter Perkins, Sabrina Reis, Zayd Hammoudeh, Daniel Lowd, Sameer Singh
What Models Know About Their Attackers: Deriving Attacker Information From Latent Representations. BlackboxNLP@EMNLP (2021)
Jonathan Brophy, Daniel Lowd
Machine Unlearning for Random Forests. ICML (2021)
Jonathan Brophy, Daniel Lowd
DART: Data Addition and Removal Trees. CoRR (2020)
Soheil Jamshidi, Zayd Hammoudeh, Ramakrishnan Durairajan, Daniel Lowd, Reza Rejaie, Walter Willinger
On the Practicality of Learning Models for Network Telemetry. TMA (2020)
Zayd Hammoudeh, Daniel Lowd
Learning from Positive and Unlabeled Data with Arbitrary Positive Shift. NeurIPS (2020)
Jonathan Brophy, Daniel Lowd
TREX: Tree-Ensemble Representer-Point Explanations. CoRR (2020)
Jonathan Brophy, Daniel Lowd
EGGS: A Flexible Approach to Relational Modeling of Social Network Spam. CoRR (2020)
Zayd Hammoudeh, Daniel Lowd
Learning from Positive and Unlabeled Data with Arbitrary Positive Shift. CoRR (2020)
Pedro M. Domingos, Daniel Lowd
Unifying logical and statistical AI with Markov logic. Commun. ACM 62 (7) (2019)
Javid Ebrahimi, Daniel Lowd, Dejing Dou
On Adversarial Examples for Character-Level Neural Machine Translation. COLING (2018)
Javid Ebrahimi, Anyi Rao, Daniel Lowd, Dejing Dou
HotFlip: White-Box Adversarial Examples for Text Classification. ACL (2) (2018)
Javid Ebrahimi, Daniel Lowd, Dejing Dou
On Adversarial Examples for Character-Level Neural Machine Translation. CoRR (2018)
Javid Ebrahimi, Anyi Rao, Daniel Lowd, Dejing Dou
HotFlip: White-Box Adversarial Examples for NLP. CoRR (2017)
Amir Pouran Ben Veyseh, Javid Ebrahimi, Dejing Dou, Daniel Lowd
A Temporal Attentional Model for Rumor Stance Classification. CIKM (2017)
Jonathan Brophy, Daniel Lowd
Collective Classification of Social Network Spam. AAAI Workshops (2017)
Tarek R. Besold, Artur S. d'Avila Garcez, Sebastian Bader, Howard Bowman, Pedro M. Domingos, Pascal Hitzler, Kai-Uwe Kühnberger, Luís C. Lamb, Daniel Lowd, Priscila Machado Vieira Lima, Leo de Penning, Gadi Pinkas, Hoifung Poon, Gerson Zaverucha
Neural-Symbolic Learning and Reasoning: A Survey and Interpretation. CoRR (2017)
Shangpu Jiang, Daniel Lowd, Dejing Dou
A Probabilistic Approach to Knowledge Translation. AAAI (2016)
Amirmohammad Rooshenas, Daniel Lowd
Discriminative Structure Learning of Arithmetic Circuits. AISTATS (2016)
Shangpu Jiang, Daniel Lowd, Sabin Kafle, Dejing Dou
Ontology Matching with Knowledge Rules. Trans. Large Scale Data Knowl. Centered Syst. 28 (2016)
Javid Ebrahimi, Dejing Dou, Daniel Lowd
A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets. COLING (2016)
Hao Wang, Dejing Dou, Daniel Lowd
Ontology-Based Deep Restricted Boltzmann Machine. DEXA (1) (2016)
Javid Ebrahimi, Dejing Dou, Daniel Lowd
Weakly Supervised Tweet Stance Classification by Relational Bootstrapping. EMNLP (2016)
Amirmohammad Rooshenas, Daniel Lowd
Discriminative Structure Learning of Arithmetic Circuits. AAAI (2016)
Pedro M. Domingos, Daniel Lowd, Stanley Kok, Aniruddh Nath, Hoifung Poon, Matthew Richardson, Parag Singla
Unifying Logical and Statistical AI. LICS (2016)
Igor Burago, Daniel Lowd
Automated Attacks on Compression-Based Classifiers. AISec@CCS (2015)
Daniel Lowd, Amirmohammad Rooshenas
The Libra toolkit for probabilistic models. J. Mach. Learn. Res. 16 (2015)
Shangpu Jiang, Daniel Lowd, Dejing Dou
A Probabilistic Approach to Knowledge Translation. CoRR (2015)
Shangpu Jiang, Daniel Lowd, Dejing Dou
Ontology Matching with Knowledge Rules. CoRR (2015)
Shangpu Jiang, Daniel Lowd, Dejing Dou
Ontology Matching with Knowledge Rules. DEXA (1) (2015)
Daniel Lowd, Amirmohammad Rooshenas
The Libra Toolkit for Probabilistic Models. CoRR (2015)
MohamadAli Torkamani, Daniel Lowd
On Robustness and Regularization of Structural Support Vector Machines. ICML (2014)
Daniel Lowd, Brenton Lessley, Mino De Raj
Towards Adversarial Reasoning in Statistical Relational Domains. AAAI Workshop: Statistical Relational Artificial Intelligence (2014)
Adam Bates, Ryan Leonard, Hannah Pruse, Daniel Lowd, Kevin R. B. Butler
Leveraging USB to Establish Host Identity Using Commodity Devices. NDSS (2014)
Amirmohammad Rooshenas, Daniel Lowd
Learning Sum-Product Networks with Direct and Indirect Variable Interactions. ICML (2014)
Reza Motamedi, Reza Rejaie, Walter Willinger, Daniel Lowd, Roberto Gonzalez
Inferring coarse views of connectivity in very large graphs. COSN (2014)
Daniel Lowd, Jesse Davis
Improving Markov network structure learning using decision trees. J. Mach. Learn. Res. 15 (1) (2014)
MohamadAli Torkamani, Daniel Lowd
Convex Adversarial Collective Classification. ICML (1) (2013)
Amirmohammad Rooshenas, Daniel Lowd
Learning Tractable Graphical Models Using Mixture of Arithmetic Circuits. AAAI (Late-Breaking Developments) (2013)
Daniel Lowd, Amirmohammad Rooshenas
Learning Markov Networks With Arithmetic Circuits. AISTATS (2013)
David Stevens, Daniel Lowd
On the hardness of evading combinations of linear classifiers. AISec (2013)
Daniel Lowd
Closed-Form Learning of Markov Networks from Dependency Networks CoRR (2012)
Daniel Lowd, Pedro M. Domingos
Learning Arithmetic Circuits CoRR (2012)
MohamadAli Torkamani, Daniel Lowd
Convex Adversarial Collective Classification. StarAI@UAI (2012)
Shangpu Jiang, Daniel Lowd, Dejing Dou
Using Markov Logic to Refine an Automatically Extracted Knowledge Base. StarAI@UAI (2012)
Shangpu Jiang, Daniel Lowd, Dejing Dou
Learning to Refine an Automatically Extracted Knowledge Base Using Markov Logic. ICDM (2012)
Daniel Lowd
Closed-Form Learning of Markov Networks from Dependency Networks. UAI (2012)
Daniel Lowd, Arash Shamaei
Mean Field Inference in Dependency Networks: An Empirical Study. AAAI (2011)
Daniel Lowd, Jesse Davis
Learning Markov Network Structure with Decision Trees. ICDM (2010)
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)
Daniel Lowd, Pedro M. Domingos
Approximate Inference by Compilation to Arithmetic Circuits. NIPS (2010)
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)
Daniel Lowd, Nicholas Kushmerick
Using salience to segment desktop activity into projects. IUI (2009)
Pedro M. 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)
Daniel Lowd, Pedro M. Domingos
Learning Arithmetic Circuits. UAI (2008)
Pedro M. Domingos, Daniel Lowd, Stanley Kok, Hoifung Poon, Matthew Richardson, Parag Singla
Just Add Weights: Markov Logic for the Semantic Web. URSW (LNCS Vol.) (2008)
Daniel Lowd, Pedro M. Domingos
Efficient Weight Learning for Markov Logic Networks. PKDD (2007)
Daniel Lowd, Pedro M. Domingos
Recursive Random Fields. IJCAI (2007)
Daniel Lowd, Christopher Meek
Adversarial learning. KDD (2005)
Daniel Lowd, Christopher Meek
Good Word Attacks on Statistical Spam Filters. CEAS (2005)
Daniel Lowd, Pedro M. Domingos
Naive Bayes models for probability estimation. ICML (2005)