Daniel Lowd - RankMe

83 papers A* 18A 6B 3Journal 29Unranked 24

Year	Rank	Type	Title / Venue / Authors
2025	B	`conf`	On the Practicality of Differential Privacy for Knowledge Tracing. EDM Anika Kabir, Chandan Tankala, Daniel Lowd
2025	—	`conf`	The Ultimate Cookbook for Invisible Poison: Crafting Subtle Clean-Label Text Backdoors with Style Attributes. SaTML Wencong You, Daniel Lowd
2025	J	`jnl`	The Ultimate Cookbook for Invisible Poison: Crafting Subtle Clean-Label Text Backdoors with Style Attributes. CoRR Wencong You, Daniel Lowd
2024	J	`jnl`	MaPPing Your Model: Assessing the Impact of Adversarial Attacks on LLM-based Programming Assistants. CoRR John Heibel, Daniel Lowd
2024	A*	`conf`	Provable Robustness against a Union of L_0 Adversarial Attacks. AAAI Zayd Hammoudeh, Daniel Lowd
2024	J	`jnl`	Training data influence analysis and estimation: a survey. Mach. Learn. Zayd Hammoudeh, Daniel Lowd
2023	J	`jnl`	Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees. J. Mach. Learn. Res. Jonathan Brophy, Zayd Hammoudeh, Daniel Lowd
2023	J	`jnl`	Feature Partition Aggregation: A Fast Certified Defense Against a Union of Sparse Adversarial Attacks. CoRR Zayd Hammoudeh, Daniel Lowd
2023	—	`conf`	Large Language Models Are Better Adversaries: Exploring Generative Clean-Label Backdoor Attacks Against Text Classifiers. EMNLP (Findings) Wencong You, Zayd Hammoudeh, Daniel Lowd
2023	J	`jnl`	Large Language Models Are Better Adversaries: Exploring Generative Clean-Label Backdoor Attacks Against Text Classifiers. CoRR Wencong You, Zayd Hammoudeh, Daniel Lowd
2023	—	`conf`	Reducing Certified Regression to Certified Classification for General Poisoning Attacks. SaTML Zayd Hammoudeh, Daniel Lowd
2022	J	`jnl`	Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees. CoRR Jonathan Brophy, Zayd Hammoudeh, Daniel Lowd
2022	J	`jnl`	Identifying Adversarial Attacks on Text Classifiers. CoRR Zhouhang Xie, Jonathan Brophy, Adam Noack, Wencong You, Kalyani Asthana, Carter Perkins, Sabrina Reis, Sameer Singh, Daniel Lowd
2022	A*	`conf`	Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation. CCS Zayd Hammoudeh, Daniel Lowd
2022	J	`jnl`	Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation. CoRR Zayd Hammoudeh, Daniel Lowd
2022	A*	`conf`	Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees. NeurIPS Jonathan Brophy, Daniel Lowd
2022	J	`jnl`	Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees. CoRR Jonathan Brophy, Daniel Lowd
2022	J	`jnl`	Reducing Certified Regression to Certified Classification. CoRR Zayd Hammoudeh, Daniel Lowd
2022	J	`jnl`	TCAB: A Large-Scale Text Classification Attack Benchmark. CoRR Kalyani Asthana, Zhouhang Xie, Wencong You, Adam Noack, Jonathan Brophy, Sameer Singh, Daniel Lowd
2022	J	`jnl`	Training Data Influence Analysis and Estimation: A Survey. CoRR Zayd Hammoudeh, Daniel Lowd
2021	A*	`conf`	Machine Unlearning for Random Forests. ICML Jonathan Brophy, Daniel Lowd
2021	—	`conf`	What Models Know About Their Attackers: Deriving Attacker Information From Latent Representations. BlackboxNLP@EMNLP Zhouhang Xie, Jonathan Brophy, Adam Noack, Wencong You, Kalyani Asthana, Carter Perkins, Sabrina Reis, Zayd Hammoudeh, Daniel Lowd, Sameer Singh
2020	J	`jnl`	DART: Data Addition and Removal Trees. CoRR Jonathan Brophy, Daniel Lowd
2020	J	`jnl`	EGGS: A Flexible Approach to Relational Modeling of Social Network Spam. CoRR Jonathan Brophy, Daniel Lowd
2020	A*	`conf`	Learning from Positive and Unlabeled Data with Arbitrary Positive Shift. NeurIPS Zayd Hammoudeh, Daniel Lowd
2020	J	`jnl`	Learning from Positive and Unlabeled Data with Arbitrary Positive Shift. CoRR Zayd Hammoudeh, Daniel Lowd
2020	—	`conf`	On the Practicality of Learning Models for Network Telemetry. TMA Soheil Jamshidi, Zayd Hammoudeh, Ramakrishnan Durairajan, Daniel Lowd, Reza Rejaie, Walter Willinger
2020	J	`jnl`	TREX: Tree-Ensemble Representer-Point Explanations. CoRR Jonathan Brophy, Daniel Lowd
2019	J	`jnl`	Unifying logical and statistical AI with Markov logic. Commun. ACM Pedro M. Domingos, Daniel Lowd
2018	—	`conf`	HotFlip: White-Box Adversarial Examples for Text Classification. ACL (2) Javid Ebrahimi, Anyi Rao, Daniel Lowd, Dejing Dou
2018	B	`conf`	On Adversarial Examples for Character-Level Neural Machine Translation. COLING Javid Ebrahimi, Daniel Lowd, Dejing Dou
2018	J	`jnl`	On Adversarial Examples for Character-Level Neural Machine Translation. CoRR Javid Ebrahimi, Daniel Lowd, Dejing Dou
2017	A	`conf`	A Temporal Attentional Model for Rumor Stance Classification. CIKM Amir Pouran Ben Veyseh, Javid Ebrahimi, Dejing Dou, Daniel Lowd
2017	—	`conf`	Collective Classification of Social Network Spam. AAAI Workshops Jonathan Brophy, Daniel Lowd
2017	J	`jnl`	HotFlip: White-Box Adversarial Examples for NLP. CoRR Javid Ebrahimi, Anyi Rao, Daniel Lowd, Dejing Dou
2017	J	`jnl`	Neural-Symbolic Learning and Reasoning: A Survey and Interpretation. CoRR 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
2016	B	`conf`	A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets. COLING Javid Ebrahimi, Dejing Dou, Daniel Lowd
2016	A*	`conf`	A Probabilistic Approach to Knowledge Translation. AAAI Shangpu Jiang, Daniel Lowd, Dejing Dou
2016	A*	`conf`	Discriminative Structure Learning of Arithmetic Circuits. AAAI Amirmohammad Rooshenas, Daniel Lowd
2016	A	`conf`	Discriminative Structure Learning of Arithmetic Circuits. AISTATS Amirmohammad Rooshenas, Daniel Lowd
2016	J	`jnl`	Ontology Matching with Knowledge Rules. Trans. Large Scale Data Knowl. Centered Syst. Shangpu Jiang, Daniel Lowd, Sabin Kafle, Dejing Dou
2016	—	`conf`	Ontology-Based Deep Restricted Boltzmann Machine. DEXA (1) Hao Wang, Dejing Dou, Daniel Lowd
2016	A*	`conf`	Unifying Logical and Statistical AI. LICS Pedro M. Domingos, Daniel Lowd, Stanley Kok, Aniruddh Nath, Hoifung Poon, Matthew Richardson, Parag Singla
2016	A*	`conf`	Weakly Supervised Tweet Stance Classification by Relational Bootstrapping. EMNLP Javid Ebrahimi, Dejing Dou, Daniel Lowd
2015	J	`jnl`	A Probabilistic Approach to Knowledge Translation. CoRR Shangpu Jiang, Daniel Lowd, Dejing Dou
2015	—	`conf`	Automated Attacks on Compression-Based Classifiers. AISec@CCS Igor Burago, Daniel Lowd
2015	—	`conf`	Ontology Matching with Knowledge Rules. DEXA (1) Shangpu Jiang, Daniel Lowd, Dejing Dou
2015	J	`jnl`	Ontology Matching with Knowledge Rules. CoRR Shangpu Jiang, Daniel Lowd, Dejing Dou
2015	J	`jnl`	The Libra Toolkit for Probabilistic Models. CoRR Daniel Lowd, Amirmohammad Rooshenas
2015	J	`jnl`	The Libra toolkit for probabilistic models. J. Mach. Learn. Res. Daniel Lowd, Amirmohammad Rooshenas
2014	J	`jnl`	Improving Markov network structure learning using decision trees. J. Mach. Learn. Res. Daniel Lowd, Jesse Davis
2014	—	`conf`	Inferring coarse views of connectivity in very large graphs. COSN Reza Motamedi, Reza Rejaie, Walter Willinger, Daniel Lowd, Roberto Gonzalez
2014	A*	`conf`	Learning Sum-Product Networks with Direct and Indirect Variable Interactions. ICML Amirmohammad Rooshenas, Daniel Lowd
2014	A*	`conf`	Leveraging USB to Establish Host Identity Using Commodity Devices. NDSS Adam Bates, Ryan Leonard, Hannah Pruse, Daniel Lowd, Kevin R. B. Butler
2014	A*	`conf`	On Robustness and Regularization of Structural Support Vector Machines. ICML MohamadAli Torkamani, Daniel Lowd
2014	—	`conf`	Towards Adversarial Reasoning in Statistical Relational Domains. StarAI@AAAI Daniel Lowd, Brenton Lessley, Mino De Raj
2013	—	`conf`	Convex Adversarial Collective Classification. ICML (1) MohamadAli Torkamani, Daniel Lowd
2013	A	`conf`	Learning Markov Networks With Arithmetic Circuits. AISTATS Daniel Lowd, Amirmohammad Rooshenas
2013	—	`conf`	Learning Tractable Graphical Models Using Mixture of Arithmetic Circuits. AAAI (Late-Breaking Developments) Amirmohammad Rooshenas, Daniel Lowd
2013	—	`conf`	On the hardness of evading combinations of linear classifiers. AISec David Stevens, Daniel Lowd
2012	J	`jnl`	Closed-Form Learning of Markov Networks from Dependency Networks CoRR Daniel Lowd
2012	A	`conf`	Closed-Form Learning of Markov Networks from Dependency Networks. UAI Daniel Lowd
2012	—	`conf`	Convex Adversarial Collective Classification. StarAI@UAI MohamadAli Torkamani, Daniel Lowd
2012	J	`jnl`	Learning Arithmetic Circuits CoRR Daniel Lowd, Pedro M. Domingos
2012	A*	`conf`	Learning to Refine an Automatically Extracted Knowledge Base Using Markov Logic. ICDM Shangpu Jiang, Daniel Lowd, Dejing Dou
2012	—	`conf`	Using Markov Logic to Refine an Automatically Extracted Knowledge Base. StarAI@UAI Shangpu Jiang, Daniel Lowd, Dejing Dou
2011	A*	`conf`	Mean Field Inference in Dependency Networks: An Empirical Study. AAAI Daniel Lowd, Arash Shamaei
2010	—	`conf`	Approximate Inference by Compilation to Arithmetic Circuits. NIPS Daniel Lowd, Pedro M. Domingos
2010	—	`conf`	Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. StarAI@AAAI Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik
2010	—	`conf`	Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. ECML/PKDD (2) Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik
2010	A*	`conf`	Learning Markov Network Structure with Decision Trees. ICDM Daniel Lowd, Jesse Davis
2010	—	`ch.`	Markov Logic: A Language and Algorithms for Link Mining. Link Mining Pedro M. Domingos, Daniel Lowd, Stanley Kok, Aniruddh Nath, Hoifung Poon, Matthew Richardson, Parag Singla
2009	—	`book`	Markov Logic: An Interface Layer for Artificial Intelligence Markov Logic Pedro M. Domingos, Daniel Lowd
2009	A	`conf`	Using salience to segment desktop activity into projects. IUI Daniel Lowd, Nicholas Kushmerick
2008	—	`conf`	Just Add Weights: Markov Logic for the Semantic Web. URSW (LNCS Vol.) Pedro M. Domingos, Daniel Lowd, Stanley Kok, Hoifung Poon, Matthew Richardson, Parag Singla
2008	A	`conf`	Learning Arithmetic Circuits. UAI Daniel Lowd, Pedro M. Domingos
2008	—	`ch.`	Markov Logic. Probabilistic Inductive Logic Programming Pedro M. Domingos, Stanley Kok, Daniel Lowd, Hoifung Poon, Matthew Richardson, Parag Singla
2008	—	`conf`	Markov Logic: A Unifying Language for Structural and Statistical Pattern Recognition. SSPR/SPR Pedro M. Domingos, Stanley Kok, Daniel Lowd, Hoifung Poon, Matthew Richardson, Parag Singla, Marc Sumner, Jue Wang
2007	—	`conf`	Efficient Weight Learning for Markov Logic Networks. PKDD Daniel Lowd, Pedro M. Domingos
2007	A*	`conf`	Recursive Random Fields. IJCAI Daniel Lowd, Pedro M. Domingos
2005	A*	`conf`	Adversarial learning. KDD Daniel Lowd, Christopher Meek
2005	—	`conf`	Good Word Attacks on Statistical Spam Filters. CEAS Daniel Lowd, Christopher Meek
2005	A*	`conf`	Naive Bayes models for probability estimation. ICML Daniel Lowd, Pedro M. Domingos