Machine Learning

Project Overview

We are working on core models and algorithms in machine learning.

Publications

Multi-Task Learning as Multi-Objective Optimization

Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search

Deep Fundamental Matrix Estimation

Deep Continuous Clustering

An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Robust Continuous Clustering

Parameter Learning and Convergent Inference for Dense Random Fields

Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials