b'Lu Yu'

research

∙ 05/29/2023

Volume Feature Rendering for Fast Neural Radiance Field Reconstruction

Neural radiance fields (NeRFs) are able to synthesize realistic novel vi...

0 Kang Han, et al. ∙

research

∙ 05/25/2023

Camera-Incremental Object Re-Identification with Identity Knowledge Evolution

Object Re-identification (ReID) aims to retrieve the probe object from m...

0 Hantao Yao, et al. ∙

research

∙ 04/28/2023

Quality-agnostic Image Captioning to Safely Assist People with Vision Impairment

Automated image captioning has the potential to be a useful tool for peo...

0 Lu Yu, et al. ∙

research

∙ 03/11/2023

Knowledge Distillation for Efficient Sequences of Training Runs

In many practical scenarios – like hyperparameter search or continual re...

0 Xingyu Liu, et al. ∙

research

∙ 03/08/2023

X-Pruner: eXplainable Pruning for Vision Transformers

Recently vision transformer models have become prominent models for a ra...

0 Lu Yu, et al. ∙

research

∙ 02/13/2023

DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation

In recommendation scenarios, there are two long-standing challenges, i.e...

0 Feng Zhu, et al. ∙

research

∙ 12/15/2022

SteerNeRF: Accelerating NeRF Rendering via Smooth Viewpoint Trajectory

Neural Radiance Fields (NeRF) have demonstrated superior novel view synt...

3 Sicheng Li, et al. ∙

research

∙ 09/30/2022

Task Formulation Matters When Learning Continually: A Case Study in Visual Question Answering

Continual learning aims to train a model incrementally on a sequence of ...

0 Mavina Nikandrou, et al. ∙

research

∙ 07/28/2022

Improving Few-shot News Recommendation via Cross-lingual Transfer

The cold-start problem has been commonly recognized in recommendation sy...

0 Taicheng Guo, et al. ∙

research

∙ 07/12/2022

eX-ViT: A Novel eXplainable Vision Transformer for Weakly Supervised Semantic Segmentation

Recently vision transformer models have become prominent models for a ra...

0 Lu Yu, et al. ∙

research

∙ 07/06/2022

Adversarial Robustness of Visual Dialog

Adversarial robustness evaluates the worst-case performance scenario of ...

0 Lu Yu, et al. ∙

research

∙ 02/23/2022

Mirror Descent Strikes Again: Optimal Stochastic Convex Optimization under Infinite Noise Variance

We study stochastic convex optimization under infinite noise variance. S...

0 Nuri Mert Vural, et al. ∙

research

∙ 01/05/2022

Group structure estimation for panel data – a general approach

Consider a panel data setting where repeated observations on individuals...

0 Lu Yu, et al. ∙

research

∙ 12/30/2021

Continually Learning Self-Supervised Representations with Projected Functional Regularization

Recent self-supervised learning methods are able to learn high-quality i...

0 Alex Gomez-Villa, et al. ∙

research

∙ 09/13/2021

Scrybe: A Secure Audit Trail for Clinical Trial Data Fusion

Clinical trials are a multi-billion dollar industry. One of the biggest ...

0 Jon Oakley, et al. ∙

research

∙ 07/28/2021

Subjective evaluation of traditional and learning-based image coding methods

We conduct a subjective experiment to compare the performance of traditi...

0 Zhigao Fang, et al. ∙

research

∙ 12/06/2020

Self-Training for Class-Incremental Semantic Segmentation

We study incremental learning for semantic segmentation where when learn...

0 Lu Yu, et al. ∙

research

∙ 11/11/2020

DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANs

Image-to-image translation has recently achieved remarkable results. But...

0 Yaxing Wang, et al. ∙

research

∙ 09/16/2020

Compressing Facial Makeup Transfer Networks by Collaborative Distillation and Kernel Decomposition

Although the facial makeup transfer network has achieved high-quality pe...

0 Bianjiang Yang, et al. ∙

research

∙ 09/02/2020

Self-supervised Smoothing Graph Neural Networks

This paper studies learning node representations with GNNs for unsupervi...

16 Lu Yu, et al. ∙

research

∙ 06/14/2020

An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias

Structured non-convex learning problems, for which critical points have ...

0 Lu Yu, et al. ∙

research

∙ 05/19/2020

Addressing Class-Imbalance Problem in Personalized Ranking

Pairwise ranking models have been widely used to address recommendation ...

1 Lu Yu, et al. ∙

research

∙ 04/01/2020

Semantic Drift Compensation for Class-Incremental Learning

Class-incremental learning of deep networks sequentially increases the n...

0 Lu Yu, et al. ∙

research

∙ 02/25/2020

Protocol Proxy: An FTE-based Covert Channel

In a hostile network environment, users must communicate without being d...

0 Jonathan Oakley, et al. ∙

research

∙ 10/15/2019

Privacy Preserving Count Statistics

The ability to preserve user privacy and anonymity is important. One of ...

0 Lu Yu, et al. ∙

research

∙ 07/08/2019

False Discovery Rates in Biological Networks

The increasing availability of data has generated unprecedented prospect...

0 Lu Yu, et al. ∙

research

∙ 04/07/2019

Learning Metrics from Teachers: Compact Networks for Image Embedding

Metric learning networks are used to compute image embeddings, which are...

0 Lu Yu, et al. ∙

research

∙ 05/11/2018

Weakly Supervised Domain-Specific Color Naming Based on Attention

The majority of existing color naming methods focuses on the eleven basi...

0 Lu Yu, et al. ∙

research

∙ 08/01/2016

Oracle Inequalities for High-dimensional Prediction

The abundance of high-dimensional data in the modern sciences has genera...

0 Johannes Lederer, et al. ∙

Lu Yu

Featured Co-authors