6 citations · 13 across the 10 of their papers we have counts for
10 papers
RusTitW: Russian Language Text Dataset for Visual Text in-the-Wild Recognition
Igor Markov, Sergey Nesteruk, Andrey Kuznetsov +1
Information surrounds people in modern life. Text is a very efficient type of information that people use for communication for centuries. However, automated text-in-the-wild recog…
Efficient Multi-stage Inference on Tabular Data
Daniel S Johnson, Igor L Markov
Many ML applications and products train on medium amounts of input data but get bottlenecked in real-time inference. When implementing ML systems, conventional wisdom favors segreg…
Practical Knowledge Distillation: Using DNNs to Beat DNNs
Chung-Wei Lee, Pavlos Athanasios Apostolopulos, Igor L. Markov
For tabular data sets, we explore data and model distillation, as well as data denoising. These techniques improve both gradient-boosting models and a specialized DNN architecture.…
Enhancing quantum computer performance via symmetrization
Andrii Maksymov, Jason Nguyen, Yunseong Nam +1
Large quantum computers promise to solve some critical problems not solvable otherwise. However, modern quantum technologies suffer various imperfections such as control errors and…
Federated Calibration and Evaluation of Binary Classifiers
Graham Cormode, Igor Markov
We address two major obstacles to practical use of supervised classifiers on distributed private data. Whether a classifier was trained by a federation of cooperating clients or tr…
Data-Driven Mitigation of Adversarial Text Perturbation
Rasika Bhalerao, Mohammad Al-Rubaie, Anand Bhaskar +1
Social networks have become an indispensable part of our lives, with billions of people producing ever-increasing amounts of text. At such scales, content policies and their enforc…
Picasso: Model-free Feature Visualization
Binh Vu, Igor Markov
Today, Machine Learning (ML) applications can have access to tens of thousands of features. With such feature sets, efficiently browsing and curating subsets of most relevant featu…
Prioritizing Original News on Facebook
Xiuyan Ni, Shujian Bu, Igor L. Markov
This work outlines how we prioritize original news, a critical indicator of news quality. By examining the landscape and life-cycle of news posts on our social media platform, we i…
Personalization for Web-based Services using Offline Reinforcement Learning
Pavlos Athanasios Apostolopoulos, Zehui Wang, Hanson Wang +4
Large-scale Web-based services present opportunities for improving UI policies based on observed user interactions. We address challenges of learning such policies through model-fr…
Regular Expressions for Fast-response COVID-19 Text Classification
Igor L. Markov, Jacqueline Liu, Adam Vagner
Text classifiers are at the core of many NLP applications and use a variety of algorithmic approaches and software. This paper introduces infrastructure and methodologies for text…