Distributed Optimization


A Family of Tractable Graph Metrics
Jose Bento and Stratis Ioannidis.
Applied Network Science, 2019.

A Family of Tractable Graph Distances
Jose Bento and Stratis Ioannidis.
SIAM Interantional Conference on Data Mining (SDM), San Diego, CA, 2018.

Distributing Frank-Wolfe via Map-Reduce
Armin Moharrer and Stratis Ioannidis.
IEEE International Conference on Data Mining (ICDM), New Orleans, LA, 2017. [code]
Selected as one of the "Best Papers of ICDM 2017".

Parallel News-Article Traffic Forecasting with ADMM
Stratis Ioannidis, Yunjiang Jiang, Saeed Amizadeh, and Nikolay Laptev.
International Workshop on Mining and Learning from Time Series (MiLeTS), San Francisco, CA, 2016. [code]

Comparison-Based Learning

Variational Inference from Ranked Samples with Features
Yuan Guo, Jennifer Dy, Deniz Erdoğmuş, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, and Stratis Ioannidis.
Asian Conference on Machine Learning (ACML), Nagoya, Japan, 2019. [code]

Classification and Comparison via Neural Networks
İlkay Yıldız, Peng Tian, Jennifer Dy, Deniz Erdoğmuş, James Brown, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, and Stratis Ioannidis.
Elsevier Journal of Neural Networks, 2019. [code]

A Severity Score for Retinopathy of Prematurity
Peng Tian, Yuan Guo, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Jennifer Dy, Deniz Erdoğmuş, and Stratis Ioannidis.
Knowledge Discovery and Data Mining (KDD), Anchorage, AK, 2019. [code]

Accelerated Experimental Design for Pairwise Comparisons
Yuan Guo, Jennifer Dy, Deniz Erdoğmuş, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, and Stratis Ioannidis.
SIAM International Conference on Data Mining (SDM), Calgary, Alberta, Canada, 2019. [code]

Experimental Design Under the Bradley-Terry Model
Yuan Guo, Peng Tian, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Deniz Erdoğmuş, Jennifer Dy, and Stratis Ioannidis.
International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, 2018. [code]

From Small-World Networks to Comparison-Based Search
Amin Karbasi, Stratis Ioannidis, and Laurent Massoulié.
IEEE Transactions on Information Theory (IT), 2015.

Comparison-Based Learning with Rank Nets
Amin Karbasi, Stratis Ioannidis, and Laurent Massoulié.
International Conference on Machine Learning (ICML), Edinburgh, UK, 2012.

Hot or Not: Interactive Content Search Using Comparisons
Amin Karbasi, Stratis Ioannidis, and Laurent Massoulié.
Information Theory and Applications Workshop (ITA), San Diego, CA, 2012.

Content Search Through Comparisons
Amin Karbasi, Stratis Ioannidis, and Laurent Massoulie.
International Colloquium on Automata, Languages and Programming (ICALP), Zurich, Switzerland, 2011.
[Full Version]

Clustering, Learning Mixtures, & User Identification

Iterative Spectral Method for Alternative Clustering
Chieh Wu, Stratis Ioannidis, Mario Sznaier, Xiangyu Li, David Kaeli, and Jennifer Dy.
International Conference on Artificial Intelligence and Statistics (AISTATS), Playa Blanca, Spain, 2018. [Supplement]

Learning Mixtures of Linear Classifiers
Yuekai Sun, Stratis Ioannidis, and Andrea Montanari.
International Conference on Machine Learning (ICML), Beijing, China, 2014.
[Full Version]

Guess Who Rated This Movie: Identifying Users Through Subspace Clustering
Amy Zhang, Nadia Fawaz, Stratis Ioannidis, and Andrea Montanari.
Uncertainty in Artificial Intelligence (UAI), Catalina Island, CA, 2012.

Identifying Users From Their Rating Paterns
José Bento, Nadia Fawaz, Andrea Montanari, and Stratis Ioannidis.
Challenge on Context-Aware Movie Recommendations (CAMRa), collocated with Recommender Systems (RecSys), Chicago, IL, 2011.
Winner of the CAMRa 2011 Challenge.

Privacy-Preserving Machine Learning


GraphSC: Parallel Secure Computation Made Easy
Kartik Nayak, Xiao Shaun Wang, Stratis Ioannidis, Udi Weinsberg, Nina Taft, and Elaine Shi.
Symposium on Security and Privacy (S&P), San Jose, CA, 2015.

Privacy Tradeoffs in Predictive Analytics
Stratis Ioannidis, Andrea Montanari, Udi Weinsberg, Smriti Bhagat, Nadia Fawaz, and Nina Taft.
International Conference on Measurements and Modeling of Computer Systems (SIGMETRICS), Austin, TX, 2014.
[Full Version]

Privacy-Preserving Matrix Factorization
Valeria Nikolaenko, Stratis Ioannidis, Udi Weinsberg, Marc Joye, Nina Taft, and Dan Boneh.
Computer and Communications Security (CCS), Berlin, Germany, 2013.

Privacy-Preserving Ridge Regression on Hundreds of Millions of Records
Valeria Nikolaenko, Udi Weinsberg, Stratis Ioannidis, Marc Joye, Dan Boneh, and Nina Taft.
Symposium on Security and Privacy (IEEE S&P), San Francisco, CA, 2013.

Learning From Strategic Agents

Truthful Linear Regression
Rachel Cummings, Stratis Ioannidis, and Katrina Ligett.
Conference on Learning Theory (COLT), Paris, France, 2015.

Budget Feasible Mechanisms for Experimental Design
Thibaut Horel, Stratis Ioannidis, and Muthu Muthukrishnan.
Latin American Theoretical Informatics (LATIN), Montevideo, Uruguay, 2014.

Linear Regression as a Non-Cooperative Game
Stratis Ioannidis and Patrick Loiseau.
Web and Internet Economics (WINE), Cambridge, MA, 2013.

Privacy Auctions for Recommender Systems
Pranav Dandekar, Nadia Fawaz, and Stratis Ioannidis.
Web and Internet Economics (WINE), Liverpool, UK, 2012.

Privacy Auctions for Recommender Systems
Pranav Dandekar, Nadia Fawaz, and Stratis Ioannidis.
Transactions on Economics and Computation (TEAC), 2014.

Machine Learning for Health

A Quantitative Severity Scale for Retinopathy of Prematurity Using Deep Learning to Monitor Disease Regression After Treatment
Kishan Gupta, James M. Brown, Stanford Taylor, J. Peter Campbell, Susan Ostmo, R. V. Paul Chan, Jennifer Dy, Deniz Erdoğmuş, Stratis Ioannidis, Sang J. Kim, Jayashree Kalpathy-Cramer, and Michael F. Chiang.
JAMA Ophthalmology, 2019.

Monitoring Disease Progression With a Quantitative Severity Scale for Retinopathy of Prematurity Using Deep Learning
Stanford Taylor, James M. Brown, Kishan Gupta, J. Peter Campbell, Susan Ostmo, R. V. Paul Chan, Jennifer Dy, Deniz Erdoğmuş, Stratis Ioannidis, Sang J. Kim, Jayashree Kalpathy-Cramer, and Michael F. Chiang.
JAMA Ophthalmology, 2019.

Predicting Aggression to Others in Youth With Autism Using a Wearable Biosensor
Matthew S. Goodwin, Carla A. Mazefsky, Stratis Ioannidis, Deniz Erdoğmuş, and Matthew Siegel.
Autism Research, 2019.

Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks
James M. Brown, J. Peter Campbell, Andrew Beers, Ken Chang, Susan Ostmo, R. V. Paul Chan, Jennifer Dy, Deniz Erdoğmuş, Stratis Ioannidis, Jayashree Kalpathy-Cramer, and Michael F. Chiang.
JAMA Ophthalmology, 2018.

Evaluation of a Deep Learning Image Assessment System for Detecting Severe Retinopathy of Prematurity
Travis K. Redd, J. Peter Campbell, James M. Brown, Sang Jin Kim, Susan Ostmo, R. V. Paul Chan, Jennifer Dy, Deniz Erdoğmuş, Stratis Ioannidis, Jayashree Kalpathy-Cramer, and Michael F. Chiang.
British Journal of Ophthalmology, 2018.

Predicting Imminent Aggression Onset in Minimally-Verbal Youth with Autism Spectrum Disorder Using Preceding Physiological Signals
Matthew S. Goodwin, Ozan Özdenizci, Catalina Cumpanasoiu, Peng Tian, Yuan Guo, Amy Stedman, Christine Peura, Carla Mazefsky, Matthew Siegel, Deniz Erdoğmuş, and Stratis Ioannidis.
International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), New York, NY, 2018.

Time-Series Prediction of Proximal Aggression Onset in Minimally-Verbal Youth with Autism Spectrum Disorder Using Physiological Biosignals
Ozan Özdenizci, Catalina Cumpanasoiu, Carla Mazefsky, Matthew Siegel, Deniz Erdoğmuş, Stratis Ioannidis, and Matthew Goodwin.
International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Honolulu, HI, 2018.

Recommender Systems

PNP: Fast Path Ensemble Method for Movie Design
Danai Koutra, Abhilash Dighe, Smriti Bhagat, Udi Weinsberg, Stratis Ioannidis, Christos Faloutsos and Jean Bolot.
Knowledge Discovery and Data Mining (KDD), Halifax, Nova Scotia, Canada, 2017.

Optimal Recommendations under Attraction, Aversion, and Social Influence
Wei Lu, Stratis Ioannidis, Smriti Bhagat, and Laks V.S. Lakshmanan
Knowledge Discovery and Data Mining (KDD), New York, NY, 2014.

Recommending with an Agenda: Active Learning of Private Attributes using Matrix Factorization
Smriti Bhagat, Udi Weinsberg, Stratis Ioannidis, and Nina Taft.
Recommender Systems (RecSys), Foster City, CA, 2014.
[Full Version]

BlurMe: Inferring and Obfuscating User Gender Based on Ratings
Udi Weinsberg, Smriti Bhagat, Stratis Ioannidis, and Nina Taft.
Recommender Systems (RecSys), Dublin, Ireland, 2012.

Distributed Rating Prediction in User Generated Content Streams
Sibren Isaacman, Stratis Ioannidis, Augustin Chaintreau, Margaret Martonosi.
Recommender Systems (RecSys), Chicago, IL, 2011.
[Full Version]

Radio Frequency Machine Learning Systems

DeepRadioID: Real-Time Channel-Resistent Optimization of Deep Learning-based Radio Fingerprinting Algorithm
Francesco Restuccia, Salvatore D'Oro, Amani Al-Shawabka, Mauro Belgiovine, Luca Angioloni, Stratis Ioannidis, Kaushik Chowdhury, and Tommaso Melodia.
ACM International Symposium on Mobile Ad Hoc Networking and Computing (ACM MobiHoc), Catania, Italy, 2019.

ORACLE: Optimized Radio clAssification through Convolutional neuraL nEtworks
Kunal Sankhe, Mauro Belgiovine, Fan Zhou, Shamnaz Mohamed Riyaz, Stratis Ioannidis, and Kaushik Chowdhury.
IEEE International Conference on Computer Communications (INFOCOM), Paris, France, 2019.

MAC ID Spoofing-Resistant Radio Fingerprinting
Tong Jian, Bruno Costa Rendon, Andrey Gritsenko, Jennifer Dy, Kaushik Chowdhury, and Stratis Ioannidis.
IEEE Global Conference on Signal and Information Processing (GlobalSIP 2019) , Ottawa, Ontario, Canada, 2019.

Finding a ‘New’ Needle in the Haystack: Unseen Radio Detection in Large Populations Using Deep Learning
Andrey Gritsenko, Zifeng Wang, Tong Jian, Jennifer Dy, Kaushik Chowdhury, and Stratis Ioannidis.
IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN 2019) , Newark, NJ, 2019.
Best Paper Award

Spectrum Awareness at the Edge: ModulationClassification using Smartphones
Nasim Soltani, Kunal Sankhe, Stratis Ioannidis, Dheryta Jaisinghani, and Kaushik Chowdhury.
IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN 2019) , Newark, NJ, 2019.

Impairment Shift Keying: Covert Signaling by Deep Learning of Controlled Radio Imperfections
Kunal Sankhe, Francesco Restuccia, Salvatore D'Oro, Tong Jian, Zifeng Wang, Amani Al-Shawabka, Jennifer Dy, Tommaso Melodia, Stratis Ioannidis, and Kaushik Chowdhury.
IEEE/AFCEA Military Communications Conference (MILCOM 2019) , Norfolk, VA, 2019.

Deep Learning Convolutional Neural Networks for Radio Identification.
Shamnaz Riyaz, Kunal Sankhe, Stratis Ioannidis, and Kaushik Chowdhury.
IEEE Communications Magazine. 2018.

Distributed Caching

Kelly Cache Networks
Milad Mahdian, Armin Moharrer, Stratis Ioannidis, and Edmund Yeh.
IEEE International Conference on Computer Communications (INFOCOM), Paris, France, 2019.



Intermediate Data Caching Optimization for Multi-Stage and Parallel Big Data Frameworks
Zhengyu Yang, Danlin Jia, Stratis Ioannidis, Ningfang Mi, and Bo Sheng.
IEEE International Conference on Cloud Computing (CLOUD), San Francisco, CA, 2018.




Orchestrating Massively Distributed CDNs
Joe Wenjie Jiang, Stratis Ioannidis, Laurent Massoulié, and Fabio Picconi.
Conference on Emerging Network Experiments and Technologies (CoNEXT), Nice, France, 2012.

Mobile & Opportunistic Networks