Factorization in Experiment Generation. - Devika Subramanian; Joan Feigenbaum (AAAI, 1986)

The Relevance of Irrelevance. - Devika Subramanian; Michael R. Genesereth (IJCAI, 1987)

Representational Issues in Machine Learning. - Devika Subramanian (ML, 1989)

A Theory of Justified Reformulations. - Devika Subramanian (ML, 1989)

Making Situation Calculus Indexical. - Devika Subramanian; John Woodfill (KR, 1989)

A theory of justified reformulations. - Devika Subramanian (1989)

The Utility of EBL in Recursive Domain Theories. - Devika Subramanian; Ronen Feldman (AAAI, 1990)

The Common Order-Theoretic Structure of Version Spaces and ATMS's. - Carl A. Gunter; Teow-Hin Ngair; Prakash Panangaden; Devika Subramanian (AAAI, 1991)

Measuring Utility and the Design of Provably Good EBL Algorithms. - Devika Subramanian; Scott B. Hunter (ML, 1992)

Multi-media RISSC Informatics: Retrieval of Information with Simple Structural Components (Part I: The Architecture). - Daniela Rus; Devika Subramanian (CIKM, 1993)

Provably Bounded Optimal Agents. - Stuart J. Russell; Devika Subramanian; Ronald Parr (IJCAI, 1993)

Conceptual Design and Artificial Intelligence. - Devika Subramanian (IJCAI, 1993)

A Multistrategy Learning Scheme for Agent Knowledge Acquisition. - Diana F. Gordon; Devika Subramanian (Informatica (Slovenia), 1993)

The Crystallographer's Assistant. - Vanathi Gopalakrishnan; Daniel N. Hennessy; Bruce G. Buchanan; Devika Subramanian (AAAI, 1994)

Induction of Rules for Biological Macromolecular Crystallization. - Daniel N. Hennessy; Vanathi Gopalakrishnan; Bruce G. Buchanan; John M. Rosenberg; Devika Subramanian (ISMB, 1994)

Customizing Multimedia Information Access. - Daniela Rus; Devika Subramanian (ACM Comput. Surv., 1995)

Provably Bounded-Optimal Agents. - Stuart J. Russell; Devika Subramanian (J. Artif. Intell. Res., 1995)

Shifting Vocabulary Bias in Speedup Learning. - Devika Subramanian (Mach. Learn., 1995)

Sets as Anti-Chains. - Carl A. Gunter; Teow-Hin Ngair; Devika Subramanian (ASIAN, 1996)

Information Retrieval, Information Structure, and Information Agents. - Daniela Rus; Devika Subramanian (Intelligent Hypertext, 1997)

Ants and Reinforcement Learning: A Case Study in Routing in Dynamic Networks. - Devika Subramanian; Peter Druschel; Johnny Chen (IJCAI (2), 1997)

The Common Order-Theoretic Structure of Version Spaces and ATMSs. - Carl A. Gunter; Teow-Hin Ngair; Devika Subramanian (Artif. Intell., 1997)

The Relevance of Relevance (Editorial). - Devika Subramanian; Russell Greiner; Judea Pearl (Artif. Intell., 1997)

Customizing Information Capture and Access. - Daniela Rus; Devika Subramanian (ACM Trans. Inf. Syst., 1997)

An Efficient Multipath Forwarding Method. - Johnny Chen; Peter Druschel; Devika Subramanian (INFOCOM, 1998)

A New Approach to Routing with Dynamic Metrics. - Johnny Chen; Peter Druschel; Devika Subramanian (INFOCOM, 1999)

Optimizing for Reduced Code Space using Genetic Algorithms. - Keith D. Cooper; Philip J. Schielke; Devika Subramanian (Workshop on Languages, Compilers, and Tools for Embedded Systems, 1999)

Robust Localization Algorithms for an Autonomous Campus Tour Guide. - Richard Thrapp; Christian Westbrook; Devika Subramanian (ICRA, 2001)

Adaptive Optimizing Compilers for the 21st Century. - Keith D. Cooper; Devika Subramanian; Linda Torczon (J. Supercomput., 2002)

Random 3-SAT: The Plot Thickens. - Cristian Coarfa; Demetrios D. Demopoulos; Alfonso San Miguel Aguirre; Devika Subramanian; Moshe Y. Vardi (Constraints An Int. J., 2003)

Events, Patterns and Analysis: forecasting conflict in the 21st century. - Devika Subramanian; Richard Stoll (DG.O, 2004)

Finding effective compilation sequences. - L. Almagor; Keith D. Cooper; Alexander Grosul; Timothy J. Harvey; Steven W. Reeves; Devika Subramanian; Linda Torczon; Todd Waterman (LCTES, 2004)

ACME: adaptive compilation made efficient. - Keith D. Cooper; Alexander Grosul; Timothy J. Harvey; Steven W. Reeves; Devika Subramanian; Linda Torczon; Todd Waterman (LCTES, 2005)

Predicting altered pathways using extendable scaffolds. - Bradley M. Broom; T. J. McDonnell; Devika Subramanian (Int. J. Bioinform. Res. Appl., 2006)

Exploring the structure of the space of compilation sequences using randomized search algorithms. - Keith D. Cooper; Alexander Grosul; Timothy J. Harvey; Steven W. Reeves; Devika Subramanian; Linda Torczon; Todd Waterman (J. Supercomput., 2006)

Socially relevant computing. - Michael Buckley; John Nordlinger; Devika Subramanian (SIGCSE, 2008)

Learning robust cell signalling models from high throughput proteomic data. - Mitchell Koch; Bradley M. Broom; Devika Subramanian (Int. J. Bioinform. Res. Appl., 2009)

AI Theory and Practice: A Discussion on Hard Challenges and Opportunities Ahead. - Eric Horvitz; Lise Getoor; Carlos Guestrin; James A. Hendler; Joseph A. Konstan; Devika Subramanian; Michael P. Wellman; Henry A. Kautz (AI Mag., 2010)

New components of the Dictyostelium PKA pathway revealed by Bayesian analysis of expression data. - Anup Parikh; Eryong Huang; Christopher Dinh; Blaz Zupan; Adam Kuspa; Devika Subramanian; Gad Shaulsky (BMC Bioinform., 2010)

Structural Organization of Functional Networks from EEG Signals during Motor Learning Tasks. - Fabrizio de Vico Fallani; Farhan Baluch; Laura Astolfi; Devika Subramanian; George Zouridakis; Fabio Babiloni (Int. J. Bifurc. Chaos, 2010)

Performance assessment of topologically diverse power systems subjected to hurricane events. - James Winkler; Leonardo Dueñas-Osorio; Robert Stein; Devika Subramanian (Reliab. Eng. Syst. Saf., 2010)

MEDRank: Using graph-based concept ranking to index biomedical texts. - Jorge R. Herskovic; Trevor Cohen; Devika Subramanian; M. Sriram Iyengar; Jack W. Smith; Elmer V. Bernstam (Int. J. Medical Informatics, 2011)

Model averaging strategies for structure learning in Bayesian networks with limited data. - Bradley M. Broom; Kim-Anh Do; Devika Subramanian (BMC Bioinform., 2012)

Graph-based signal integration for high-throughput phenotyping. - Jorge R. Herskovic; Devika Subramanian; Trevor Cohen; Pamela A. Bozzo-Silva; Charles F. Bearden; Elmer V. Bernstam (BMC Bioinform., 2012)

Model AI Assignments 2013. - Todd W. Neller; Marc Lanctot; Devika Subramanian; Stephanie E. August (EAAI, 2013)

Known Unknowns: An Analysis of Twitter Censorship in Turkey. - Rima S. Tanash; Zhouhan Chen; Tanmay Thakur; Dan S. Wallach; Devika Subramanian (WPES@CCS, 2015)

Classification-by-Analogy: Using Vector Representations of Implicit Relationships to Identify Plausibly Causal Drug/Side-effect Relationships. - Justin Mower; Devika Subramanian; Ning Shang; Trevor Cohen (AMIA, 2016)

Hunting Malicious Bots on Twitter: An Unsupervised Approach. - Zhouhan Chen; Rima S. Tanash; Richard Stoll; Devika Subramanian (SocInfo (2), 2017)

Text mining and network analysis to find functional associations of genes in high altitude diseases. - Balu Bhasuran; Devika Subramanian; Jeyakumar Natarajan (Comput. Biol. Chem., 2018)

An Unsupervised Approach to Detect Spam Campaigns that Use Botnets on Twitter. - Zhouhan Chen; Devika Subramanian (CoRR, 2018)

Learning predictive models of drug side-effect relationships from distributed representations of literature-derived semantic predications. - Justin Mower; Devika Subramanian; Trevor Cohen (J. Am. Medical Informatics Assoc., 2018)

Predicting Adverse Drug-Drug Interactions with Neural Embedding of Semantic Predications. - Hannah A. Burkhardt; Devika Subramanian; Justin Mower; Trevor A. Cohen (AMIA, 2019)

Complementing Observational Signal with Distributed Representations for Drug Side-effect Prediction. - Justin Mower; Trevor A. Cohen; Devika Subramanian (AMIA, 2019)

aer2vec: Distributed Representations of Adverse Event Reporting System Data as a Means to Identify Drug/Side-Effect Associations. - Jake Portanova; Nathan Murray; Justin Mower; Devika Subramanian; Trevor A. Cohen (AMIA, 2019)

Data-driven prediction of a multi-scale Lorenz 96 chaotic system using a hierarchy of deep learning methods: Reservoir computing, ANN, and RNN-LSTM. - Ashesh Chattopadhyay; Pedram Hassanzadeh; Krishna V. Palem; Devika Subramanian (CoRR, 2019)

Augmenting aer2vec: Enriching distributed representations of adverse event report data with orthographic and lexical information. - Xiruo Ding; Justin Mower; Devika Subramanian; Trevor Cohen (J. Biomed. Informatics, 2021)

Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates. - Tongtong Huang; Yan Chu 005; Shayan Shams; Yejin Kim 001; Ananth V. Annapragada; Devika Subramanian; Ioannis A. Kakadiaris; Assaf Gottlieb; Xiaoqian Jiang (J. Biomed. Informatics, 2021)

Predicting Drug Blood-Brain Barrier Penetration with Adverse Event Report Embeddings. - YiFan Wu; Justin Mower; Xiruo Ding; Oliver Li; Devika Subramanian; Trevor Cohen (AMIA, 2022)

Self-Supervised Learning for Building Robust Pediatric Chest X-ray Classification Models. - Sheng Cheng; Zbigniew Starosolski; Devika Subramanian (CoRR, 2024)