Huu Le

Unsupervised Learning for Maximum Consensus Robust Fitting: A Reinforcement Learning Approach

Exploiting Redundancy for Large Scale Bundle Adjustment: In Partial Defense of Minimization by Alternation

AdaSTE: An Adaptive Straight-Through Estimator to Train Binary Neural Networks

2021

Dyglip: A dynamic graph model with link prediction for accurate multi-camera multiple object tracking

Robust Fitting with Truncated Least Squares: A Bilevel Optimization Approach

Progressive Batching for Efficient Non-linear Least Squares

Deterministic Approximate Methods for Maximum Consensus Robust Fitting

Unsupervised Learning for Robust Fitting: A Reinforcement Learning Approach

Truncated Inference for Latent Variable Optimization Problems: Application to Robust Estimation and Learning

A Graduated Filter Method for Large Scale Robust Estimation

Simultaneous compression and quantization: A joint approach for efficient unsupervised hashing

Simultaneous feature aggregating and hashing for compact binary code learning