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10/19/2022
Identifying the Impact of User Reviews on App Updates: An Exploratory Study on App Release Notes
Release planning for mobile apps has recently become an area of active r...
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10/17/2022
The Role of User Reviews in App Updates: A Preliminary Investigation on App Release Notes
Release planning for mobile apps has recently become an area of active r...
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09/26/2022
Knowledge Distillation to Ensemble Global and Interpretable Prototype-Based Mammogram Classification Models
State-of-the-art (SOTA) deep learning mammogram classifiers, trained wit...
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09/21/2022
Multi-view Local Co-occurrence and Global Consistency Learning Improve Mammogram Classification Generalisation
When analysing screening mammograms, radiologists can naturally process ...
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09/20/2022
Collaborative Anomaly Detection
In recommendation systems, items are likely to be exposed to various use...
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08/25/2022
DPAUC: Differentially Private AUC Computation in Federated Learning
Federated learning (FL) has gained significant attention recently as a p...
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07/25/2022
REPNP: Plug-and-Play with Deep Reinforcement Learning Prior for Robust Image Restoration
Image restoration schemes based on the pre-trained deep models have rece...
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06/16/2022
Differentially Private Multi-Party Data Release for Linear Regression
Differentially Private (DP) data release is a promising technique to dis...
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05/24/2022
Differentially Private AUC Computation in Vertical Federated Learning
Federated learning has gained great attention recently as a privacy-enha...
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04/10/2022
Linear Complexity Randomized Self-attention Mechanism
Recently, random feature attentions (RFAs) are proposed to approximate t...
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03/28/2022
Translation Consistent Semi-supervised Segmentation for 3D Medical Images
3D medical image segmentation methods have been successful, but their de...
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03/04/2022
Differentially Private Label Protection in Split Learning
Split learning is a distributed training framework that allows multiple ...
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03/02/2022
Label Leakage and Protection from Forward Embedding in Vertical Federated Learning
Vertical federated learning (vFL) has gained much attention and been dep...
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03/02/2022
Counterfactually Evaluating Explanations in Recommender Systems
Modern recommender systems face an increasing need to explain their reco...
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01/28/2022
Learning to Simulate Unseen Physical Systems with Graph Neural Networks
Simulation of the dynamics of physical systems is essential to the devel...
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11/30/2021
Learning Large-Time-Step Molecular Dynamics with Graph Neural Networks
Molecular dynamics (MD) simulation predicts the trajectory of atoms by s...
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10/25/2021
Nonuniform Negative Sampling and Log Odds Correction with Rare Events Data
We investigate the issue of parameter estimation with nonuniform negativ...
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09/02/2021
Heterogeneous relational message passing networks for molecular dynamics simulations
With many frameworks based on message passing neural networks proposed t...
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08/04/2021
Dynamic Relevance Learning for Few-Shot Object Detection
Expensive bounding-box annotations have limited the development of objec...
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08/04/2021
The Impact of Traceability on Software Maintenance and Evolution: A Mapping Study
Software traceability plays a critical role in software maintenance and ...
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07/21/2021
Defending against Reconstruction Attack in Vertical Federated Learning
Recently researchers have studied input leakage problems in Federated Le...
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07/15/2021
Characteristics and Challenges of Low-Code Development: The Practitioners' Perspective
Background: In recent years, Low-code development (LCD) is growing rapid...
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06/12/2021
AutoLoss: Automated Loss Function Search in Recommendations
Designing an effective loss function plays a crucial role in training de...
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06/10/2021
Vertical Federated Learning without Revealing Intersection Membership
Vertical Federated Learning (vFL) allows multiple parties that own diffe...
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04/06/2021
Efficient state and parameter estimation for high-dimensional nonlinear system identification with application to MEG brain network modeling
System identification poses a significant bottleneck to characterizing a...
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02/17/2021
Label Leakage and Protection in Two-party Split Learning
In vertical federated learning, two-party split learning has become an i...
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01/08/2021
Symmetry-adapted graph neural networks for constructing molecular dynamics force fields
Molecular dynamics is a powerful simulation tool to explore material pro...
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10/14/2020
Towards the Transportation Internet: Concepts, Architectures and Requirements
The Internet has become a general network design paradigm. The Energy In...
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08/23/2020
Towards Earnings Call and Stock Price Movement
Earnings calls are hosted by management of public companies to discuss t...
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07/12/2020
Deep Retrieval: An End-to-End Learnable Structure Model for Large-Scale Recommendations
One of the core problems in large-scale recommendations is to retrieve t...
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02/26/2020
AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations
Deep learning based recommender systems (DLRSs) often have embedding lay...
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01/30/2020
Learning to Structure Long-term Dependence for Sequential Recommendation
Sequential recommendation recommends items based on sequences of users' ...
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11/07/2019
Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing
Many multi-domain neural machine translation (NMT) models achieve knowle...
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08/12/2019
Feature Partitioning for Efficient Multi-Task Architectures
Multi-task learning holds the promise of less data, parameters, and time...
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04/26/2019
Neural Logic Machines
We propose the Neural Logic Machine (NLM), a neural-symbolic architectur...
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04/12/2019
Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentation
Accurate multi-organ abdominal CT segmentation is essential to many clin...
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01/30/2019
Doubly Sparse: Sparse Mixture of Sparse Experts for Efficient Softmax Inference
Computations for the softmax function are significantly expensive when t...
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11/06/2018
Neural Phrase-to-Phrase Machine Translation
In this paper, we propose Neural Phrase-to-Phrase Machine Translation (N...
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10/10/2018
Fully Supervised Speaker Diarization
In this paper, we propose a fully supervised speaker diarization approac...
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10/09/2018
Rate Distortion For Model Compression: From Theory To Practice
As the size of neural network models increases dramatically today, study...
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04/20/2018
Subgoal Discovery for Hierarchical Dialogue Policy Learning
Developing conversational agents to engage in complex dialogues is chall...
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03/10/2018
Attention-based Graph Neural Network for Semi-supervised Learning
Recently popularized graph neural networks achieve the state-of-the-art ...
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11/17/2017
Thoracic Disease Identification and Localization with Limited Supervision
Accurate identification and localization of abnormalities from radiology...
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09/09/2017
How to Train Triplet Networks with 100K Identities?
Training triplet networks with large-scale data is challenging in face r...
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09/09/2017
Model Distillation with Knowledge Transfer from Face Classification to Alignment and Verification
Knowledge distillation is a potential solution for model compression. Th...
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06/17/2017
Towards Neural Phrase-based Machine Translation
In this paper, we present Neural Phrase-based Machine Translation (NPMT)...
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02/28/2017
Scaffolding Networks: Incremental Learning and Teaching Through Questioning
We introduce a new paradigm of learning for reasoning, understanding, an...
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02/24/2017
Sequence Modeling via Segmentations
Segmental structure is a common pattern in many types of sequences such ...
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11/05/2016
TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency
In this paper, we propose TopicRNN, a recurrent neural network (RNN)-bas...
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12/10/2015