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05/26/2023
COMCAT: Towards Efficient Compression and Customization of Attention-Based Vision Models
Attention-based vision models, such as Vision Transformer (ViT) and its ...
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04/27/2023
Human-machine knowledge hybrid augmentation method for surface defect detection based few-data learning
Visual-based defect detection is a crucial but challenging task in indus...
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01/20/2023
HALOC: Hardware-Aware Automatic Low-Rank Compression for Compact Neural Networks
Low-rank compression is an important model compression strategy for obta...
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12/05/2022
Algorithm and Hardware Co-Design of Energy-Efficient LSTM Networks for Video Recognition with Hierarchical Tucker Tensor Decomposition
Long short-term memory (LSTM) is a type of powerful deep neural network ...
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05/30/2022
RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression
Data imbalance, in which a plurality of the data samples come from a sma...
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02/21/2022
GIFT: Graph-guIded Feature Transfer for Cold-Start Video Click-Through Rate Prediction
Short video has witnessed rapid growth in China and shows a promising ma...
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12/15/2021
N3H-Core: Neuron-designed Neural Network Accelerator via FPGA-based Heterogeneous Computing Cores
Accelerating the neural network inference by FPGA has emerged as a popul...
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10/25/2021
MUSE: Feature Self-Distillation with Mutual Information and Self-Information
We present a novel information-theoretic approach to introduce dependenc...
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04/02/2021
GRN: Generative Rerank Network for Context-wise Recommendation
Reranking is attracting incremental attention in the recommender systems...
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02/25/2021
Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data
Learning from heterogeneous data poses challenges such as combining data...
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02/24/2021
Revisit Recommender System in the Permutation Prospective
Recommender systems (RS) work effective at alleviating information overl...
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12/22/2020
Personalized Adaptive Meta Learning for Cold-start User Preference Prediction
A common challenge in personalized user preference prediction is the col...
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11/27/2020
Multi-task MR Imaging with Iterative Teacher Forcing and Re-weighted Deep Learning
Noises, artifacts, and loss of information caused by the magnetic resona...
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11/09/2020
Distant Supervision for E-commerce Query Segmentation via Attention Network
The booming online e-commerce platforms demand highly accurate approache...
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08/19/2020
Balanced Order Batching with Task-Oriented Graph Clustering
Balanced order batching problem (BOBP) arises from the process of wareho...
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05/18/2020
EdgeRec: Recommender System on Edge in Mobile Taobao
Recommender system (RS) has become crucial module in commercial systems....
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10/13/2019
Parameter Constrained Transfer Learning for Low Dose PET Image Denoising
Positron emission tomography (PET) is widely used in clinical practice. ...
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10/08/2019
Conceptualize and Infer User Needs in E-commerce
Understanding latent user needs beneath shopping behaviors is critical t...
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06/24/2019
Query-based Interactive Recommendation by Meta-Path and Adapted Attention-GRU
Recently, interactive recommender systems are becoming increasingly popu...
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05/17/2019
Exact-K Recommendation via Maximal Clique Optimization
This paper targets to a novel but practical recommendation problem named...
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04/03/2019
Multi-Modal Generative Adversarial Network for Short Product Title Generation in Mobile E-Commerce
Nowadays, more and more customers browse and purchase products in favor ...
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11/11/2018
Product Title Refinement via Multi-Modal Generative Adversarial Learning
Nowadays, an increasing number of customers are in favor of using E-comm...
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10/08/2018
Query Tracking for E-commerce Conversational Search: A Machine Comprehension Perspective
With the development of dialog techniques, conversational search has att...
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03/30/2018
Automatic Generation of Chinese Short Product Titles for Mobile Display
This paper studies the problem of automatically extracting a short title...
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03/30/2018
Deep Cascade Multi-task Learning for Slot Filling in Chinese E-commerce Shopping Guide Assistant
Slot filling is a critical task in natural language understanding (NLU) ...
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03/02/2018
