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06/27/2023
FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer
Federated Learning (FL) has been widely concerned for it enables decentr...
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06/20/2023
PyRCA: A Library for Metric-based Root Cause Analysis
We introduce PyRCA, an open-source Python machine learning library of Ro...
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06/01/2023
OTW: Optimal Transport Warping for Time Series
Dynamic Time Warping (DTW) has become the pragmatic choice for measuring...
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04/10/2023
AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities and Challenges
Artificial Intelligence for IT operations (AIOps) aims to combine the po...
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04/04/2023
Unsupervised Brain Tumor Segmentation with Image-based Prompts
Automated brain tumor segmentation based on deep learning (DL) has achie...
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02/22/2023
HINormer: Representation Learning On Heterogeneous Information Networks with Graph Transformer
Recent studies have highlighted the limitations of message-passing based...
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01/31/2023
LogAI: A Library for Log Analytics and Intelligence
Software and System logs record runtime information about processes exec...
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09/06/2022
Continual Learning: Fast and Slow
According to the Complementary Learning Systems (CLS) theory <cit.> in n...
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07/13/2022
DeepTIMe: Deep Time-Index Meta-Learning for Non-Stationary Time-Series Forecasting
Deep learning has been actively applied to time-series forecasting, lead...
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06/03/2022
Scalar is Not Enough: Vectorization-based Unbiased Learning to Rank
Unbiased learning to rank (ULTR) aims to train an unbiased ranking model...
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03/30/2022
Continual Normalization: Rethinking Batch Normalization for Online Continual Learning
Existing continual learning methods use Batch Normalization (BN) to faci...
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02/23/2022
Learning Fast and Slow for Online Time Series Forecasting
The fast adaptation capability of deep neural networks in non-stationary...
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02/03/2022
CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting
Deep learning has been actively studied for time series forecasting, and...
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02/03/2022
ETSformer: Exponential Smoothing Transformers for Time-series Forecasting
Transformers have been actively studied for time-series forecasting in r...
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10/27/2021
Node-wise Localization of Graph Neural Networks
Graph neural networks (GNNs) emerge as a powerful family of representati...
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10/01/2021
DualNet: Continual Learning, Fast and Slow
According to Complementary Learning Systems (CLS) theory <cit.> in neuro...
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09/23/2021
Modeling Dynamic Attributes for Next Basket Recommendation
Traditional approaches to next item and next basket recommendation typic...
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09/20/2021
Merlion: A Machine Learning Library for Time Series
We introduce Merlion, an open-source machine learning library for time s...
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08/16/2021
CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation
Brain lesion segmentation provides a valuable tool for clinical diagnosi...
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10/22/2020
Learning Transferrable Parameters for Long-tailed Sequential User Behavior Modeling
Sequential user behavior modeling plays a crucial role in online user-or...
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07/30/2020
Bilevel Continual Learning
Continual learning aims to learn continuously from a stream of tasks and...
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07/17/2020
Adaptive Task Sampling for Meta-Learning
Meta-learning methods have been extensively studied and applied in compu...
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04/29/2020
UniConv: A Unified Conversational Neural Architecture for Multi-domain Task-oriented Dialogues
Building an end-to-end conversational agent for multi-domain task-orient...
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04/02/2020
MCEN: Bridging Cross-Modal Gap between Cooking Recipes and Dish Images with Latent Variable Model
Nowadays, driven by the increasing concern on diet and health, food comp...
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03/20/2020
A^2-GCN: An Attribute-aware Attentive GCN Model for Recommendation
As important side information, attributes have been widely exploited in ...
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03/09/2020
Cross-Modal Food Retrieval: Learning a Joint Embedding of Food Images and Recipes with Semantic Consistency and Attention Mechanism
Cross-modal food retrieval is an important task to perform analysis of f...
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08/23/2019
Reference Network for Neural Machine Translation
Neural Machine Translation (NMT) has achieved notable success in recent ...
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08/19/2019
Graph Neural Networks with High-order Feature Interactions
Network representation learning, a fundamental research problem which ai...
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05/09/2019
Compositional Coding for Collaborative Filtering
Efficiency is crucial to the online recommender systems. Representing us...
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05/03/2019
Learning Cross-Modal Embeddings with Adversarial Networks for Cooking Recipes and Food Images
Food computing is playing an increasingly important role in human daily ...
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10/20/2018
SL^2MF: Predicting Synthetic Lethality in Human Cancers via Logistic Matrix Factorization
Synthetic lethality (SL) is a promising concept for novel discovery of a...
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10/28/2016
