Tomo Lazovich

According to our database, Tomo Lazovich authored at least 9 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Measuring disparate outcomes of content recommendation algorithms with distributional inequality metrics.

Tomo Lazovich, Luca Belli, Aaron Gonzales, Amanda Bower, Uthaipon Tantipongpipat, Kristian Lum, Ferenc Huszár, Rumman Chowdhury

Patterns, August, 2023

Filter bubbles and affective polarization in user-personalized large language model outputs.

Tomo Lazovich

CoRR, 2023

Exposure to Marginally Abusive Content on Twitter.

Jack Bandy, Tomo Lazovich

Proceedings of the Seventeenth International AAAI Conference on Web and Social Media, 2023

TwERC: High Performance Ensembled Candidate Generation for Ads Recommendation at Twitter.

Vanessa Cai, Pradeep Prabakar, Manuel Serrano Rebuelta, Lucas Rosen, Federico Monti, Katarzyna Janocha, Tomo Lazovich, Jeetu Raj, Yedendra Shrinivasan, Hao Li, Thomas Markovich

Proceedings of the Workshop on Data Mining for Online Advertising (AdKDD 2023) co-located with the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), 2023

2022

Random Isn't Always Fair: Candidate Set Imbalance and Exposure Inequality in Recommender Systems.

Amanda Bower, Kristian Lum, Tomo Lazovich, Kyra Yee, Luca Belli

CoRR, 2022

2020

Accelerating Artificial Intelligence with Silicon Photonics.

Nicholas C. Harris, Ryan Braid, Darius Bunandar, Jim Carr, Brad Dobbie, Carlos Dorta-Quinones, Jon Elmhurst, Martin Forsythe, Michael Gould, Shashank Gupta, Sukeshwar Kannan, Tyler Kenney, Gary Kong, Tomo Lazovich, Scott Mckenzie, Carl Ramey, Chithira Ravi, Michael Scott, John Sweeney, Ozgur Yildirim, Katrina Zhang

Proceedings of the Optical Fiber Communications Conference and Exhibition, 2020

2018

Automated software vulnerability detection with machine learning.

Jacob A. Harer, Louis Y. Kim, Rebecca L. Russell, Onur Ozdemir, Leonard R. Kosta, Akshay Rangamani, Lei H. Hamilton, Gabriel I. Centeno, Jonathan R. Key, Paul M. Ellingwood, Marc W. McConley, Jeffrey M. Opper, Peter Chin, Tomo Lazovich

CoRR, 2018

Learning to Repair Software Vulnerabilities with Generative Adversarial Networks.

Jacob Harer, Onur Ozdemir, Tomo Lazovich, Christopher P. Reale, Rebecca L. Russell, Louis Y. Kim, Peter Chin

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Automated Vulnerability Detection in Source Code Using Deep Representation Learning.

Rebecca L. Russell, Louis Y. Kim, Lei H. Hamilton, Tomo Lazovich, Jacob Harer, Onur Ozdemir, Paul M. Ellingwood, Marc W. McConley

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018