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05/07/2023
Vcc: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens
Transformer models are foundational to natural language processing (NLP)...
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04/10/2023
Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition
This work proposes POMP, a prompt pre-training method for vision-languag...
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03/02/2023
Disentangling Orthogonal Planes for Indoor Panoramic Room Layout Estimation with Cross-Scale Distortion Awareness
Based on the Manhattan World assumption, most existing indoor layout est...
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02/16/2023
Decoupled Model Schedule for Deep Learning Training
Recent years have seen an increase in the development of large deep lear...
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12/21/2022
SPT: Semi-Parametric Prompt Tuning for Multitask Prompted Learning
Pre-trained large language models can efficiently interpolate human-writ...
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12/10/2022
SMILE: Scaling Mixture-of-Experts with Efficient Bi-level Routing
The mixture of Expert (MoE) parallelism is a recent advancement that sca...
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12/07/2022
Node-oriented Spectral Filtering for Graph Neural Networks
Graph neural networks (GNNs) have shown remarkable performance on homoph...
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07/04/2022
Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition
Existing out-of-distribution (OOD) detection methods are typically bench...
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07/04/2022
Removing Batch Normalization Boosts Adversarial Training
Adversarial training (AT) defends deep neural networks against adversari...
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06/15/2022
Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems
We present results from a large-scale experiment on pretraining encoders...
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04/30/2022
MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud
Existing general purpose frameworks for gigantic model training, i.e., m...
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09/24/2021
ZSD-YOLO: Zero-Shot YOLO Detection using Vision-Language KnowledgeDistillation
Real-world object sampling produces long-tailed distributions requiring ...
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07/19/2021
CETransformer: Casual Effect Estimation via Transformer Based Representation Learning
Treatment effect estimation, which refers to the estimation of causal ef...
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05/17/2021
Compressed Communication for Distributed Training: Adaptive Methods and System
Communication overhead severely hinders the scalability of distributed m...
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03/16/2021
Deep Time Series Models for Scarce Data
Time series data have grown at an explosive rate in numerous domains and...
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03/12/2021
Adversarial Graph Disentanglement
A real-world graph has a complex topology structure, which is often form...
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10/17/2020
LID 2020: The Learning from Imperfect Data Challenge Results
Learning from imperfect data becomes an issue in many industrial applica...
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10/02/2020
Taking Modality-free Human Identification as Zero-shot Learning
Human identification is an important topic in event detection, person tr...
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08/24/2020
Dynamic Dispatching for Large-Scale Heterogeneous Fleet via Multi-agent Deep Reinforcement Learning
Dynamic dispatching is one of the core problems for operation optimizati...
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07/26/2020
CSER: Communication-efficient SGD with Error Reset
The scalability of Distributed Stochastic Gradient Descent (SGD) is toda...
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06/24/2020
Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes
BERT has recently attracted a lot of attention in natural language under...
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12/04/2019
Distribution-induced Bidirectional Generative Adversarial Network for Graph Representation Learning
Graph representation learning aims to encode all nodes of a graph into l...
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10/04/2019
Manufacturing Dispatching using Reinforcement and Transfer Learning
Efficient dispatching rule in manufacturing industry is key to ensure pr...
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10/04/2019
Generative Adversarial Networks for Failure Prediction
Prognostics and Health Management (PHM) is an emerging engineering disci...
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07/11/2019
Edge Heuristic GAN for Non-uniform Blind Deblurring
Non-uniform blur, mainly caused by camera shake and motions of multiple ...
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07/09/2019
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing
We present GluonCV and GluonNLP, the deep learning toolkits for computer...
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05/27/2019
Communication-Efficient Distributed Blockwise Momentum SGD with Error-Feedback
Communication overhead is a major bottleneck hampering the scalability o...
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05/23/2019
Blockwise Adaptivity: Faster Training and Better Generalization in Deep Learning
Stochastic methods with coordinate-wise adaptive stepsize (such as RMSpr...
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04/12/2019
Remaining Useful Life Estimation Using Functional Data Analysis
Remaining Useful Life (RUL) of an equipment or one of its components is ...
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09/24/2018
Give me a hint! Navigating Image Databases using Human-in-the-loop Feedback
In this paper, we introduce an attribute-based interactive image search ...
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07/03/2018
ModaNet: A Large-Scale Street Fashion Dataset with Polygon Annotations
Understanding clothes from a single image has strong commercial and cult...
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06/08/2018
Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data
Variance reduction has been commonly used in stochastic optimization. It...
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04/13/2018
Regularized Singular Value Decomposition and Application to Recommender System
Singular value decomposition (SVD) is the mathematical basis of principa...
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04/06/2018
Minimal Support Vector Machine
Support Vector Machine (SVM) is an efficient classification approach, wh...
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03/15/2018
Fast End-to-End Trainable Guided Filter
Image processing and pixel-wise dense prediction have been advanced by h...
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11/22/2017
Conditional Image-Text Embedding Networks
This paper presents an approach for grounding phrases in images which jo...
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03/21/2017
GP-GAN: Towards Realistic High-Resolution Image Blending
Recent advances in generative adversarial networks (GANs) have shown pro...
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01/24/2017
Learning Arbitrary Pairwise Potentials in CRFs for Semantic Segmentation
Are we using the right potential functions in the Conditional Random Fie...
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10/14/2016
A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification
Linear Discriminant Analysis (LDA) is a widely-used supervised dimension...
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10/14/2016
Kernel Alignment Inspired Linear Discriminant Analysis
Kernel alignment measures the degree of similarity between two kernels. ...
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09/12/2016
Fully-Trainable Deep Matching
Deep Matching (DM) is a popular high-quality method for quasi-dense imag...
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05/04/2016
Accelerating Deep Learning with Shrinkage and Recall
Deep Learning is a very powerful machine learning model. Deep Learning t...
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04/24/2016
Stochastic Variance-Reduced ADMM
The alternating direction method of multipliers (ADMM) is a powerful opt...
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02/25/2016
Fast Nonsmooth Regularized Risk Minimization with Continuation
In regularized risk minimization, the associated optimization problem be...
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02/11/2015
Conditional Random Fields as Recurrent Neural Networks
Pixel-level labelling tasks, such as semantic segmentation, play a centr...
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10/16/2013
ImageSpirit: Verbal Guided Image Parsing
Humans describe images in terms of nouns and adjectives while algorithms...
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10/26/2010