Rishabh Iyer

Explainable AI: A Review of Machine Learning Interpretability Methods

A Genome-wide Framework for Mapping Gene Regulation via Cellular Genetic Screens

Effective gene expression prediction from sequence by integrating long-range interactions

Deep learning

Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning

A survey of deep learning techniques for autonomous driving

Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC)

Using error decay prediction to overcome practical issues of deep active learning for named entity recognition

A Survey of Deep Active Learning

Continuous space language models

Learning adaptive criteria weights for active semi-supervised learning

A Survey on Transfer Learning

Domain Adaptation for Statistical Classifiers

Distributed Representations of Words and Phrases and their Compositionality

Submodularity in Data Subset Selection and Active Learning

Relevance weighting for combining multi-domain data for -gram language modeling

Using out-of-domain data to improve in-domain language models

Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints