Learning theory and algorithms

TENSOR COMPLETION FOR EFFICIENT AND ACCURATE HYPERPARAMETER OPTIMISATION IN LARGE-SCALE STATISTICAL LEARNING

Pseudo-Inverted Bottleneck Convolution for DARTS Search Space

On the Fairness of Multitask Representation Learning

Boosting Semi-Supervised Federated Learning with Model Personalization and Client-Variance-Reduction

The Uniqueness Problem of Physical Law Learning

Feature-Rich Audio Model Inversion for Data-Free Knowledge Distillation Towards General Sound Classification

Joint Data Association, NLOS Mitigation, and Clutter Suppression for Networked Device-Free Sensing in 6G Cellular Network

ASYMMETRIC POLYNOMIAL LOSS FOR MULTI-LABEL CLASSIFICATION

An Approach to Ontological Learning from Weak Labels

Improving the Stochastic Gradient Descent's test accuracy by manipulating the l_\infty norm of its gradient approximation

Neural networks with quantization constraints.

Training Graph Neural Networks on Growing Stochastic Graphs