research
∙
09/07/2023
Exploring the Opportunities of AR for Enriching Storytelling with Family Photos between Grandparents and Grandchildren
Storytelling with family photos, as an important mode of reminiscence-ba...
share
research
∙
08/24/2023
Logic-induced Diagnostic Reasoning for Semi-supervised Semantic Segmentation
Recent advances in semi-supervised semantic segmentation have been heavi...
research
∙
08/21/2023
Towards Ubiquitous Intelligent Hand Interaction
The development of ubiquitous computing and sensing devices has brought ...
research
∙
08/21/2023
UbiPhysio: Support Daily Functioning, Fitness, and Rehabilitation with Action Understanding and Feedback in Natural Language
We introduce UbiPhysio, a milestone framework that delivers fine-grained...
research
∙
06/20/2023
LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation
Transformer models have achieved remarkable results in various natural l...
research
∙
05/30/2023
Contrastive Shapelet Learning for Unsupervised Multivariate Time Series Representation Learning
Recent studies have shown great promise in unsupervised representation l...
research
∙
03/24/2023
UniTS: A Universal Time Series Analysis Framework with Self-supervised Representation Learning
Machine learning has emerged as a powerful tool for time series analysis...
research
∙
03/06/2023
DR-Label: Improving GNN Models for Catalysis Systems by Label Deconstruction and Reconstruction
Attaining the equilibrium state of a catalyst-adsorbate system is key to...
research
∙
02/19/2023
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers
Knowledge distillation has been shown to be a powerful model compression...
research
∙
02/13/2023
Symbolic Discovery of Optimization Algorithms
We present a method to formulate algorithm discovery as program search, ...
research
∙
02/10/2023
Unified Functional Hashing in Automatic Machine Learning
The field of Automatic Machine Learning (AutoML) has recently attained i...
research
∙
10/05/2022
GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models
Prevalent semantic segmentation solutions are, in essence, a dense discr...
research
∙
10/04/2022
Less is More: Task-aware Layer-wise Distillation for Language Model Compression
Layer-wise distillation is a powerful tool to compress large models (i.e...
research
∙
09/15/2022
Multi-Task Mixture Density Graph Neural Networks for Predicting Cu-based Single-Atom Alloy Catalysts for CO2 Reduction Reaction
Graph neural networks (GNNs) have drawn more and more attention from mat...
research
∙
06/25/2022
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance
Large Transformer-based models have exhibited superior performance in va...
research
∙
05/01/2022
Temporal Events Detector for Pregnancy Care (TED-PC): A Rule-based Algorithm to Infer Gestational Age and Delivery Date from Electronic Health Records of Pregnant Women with an
Objective: To develop a rule-based algorithm that detects temporal infor...
research
∙
04/15/2022
MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation
Pre-trained language models have demonstrated superior performance in va...
research
∙
04/13/2022
CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing
Model ensemble is a popular approach to produce a low-variance and well-...
research
∙
04/11/2022
The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink
Machine Learning (ML) workloads have rapidly grown in importance, but ra...
research
∙
03/26/2022
Visual Abductive Reasoning
Abductive reasoning seeks the likeliest possible explanation for partial...
research
∙
03/18/2022
Local-Global Context Aware Transformer for Language-Guided Video Segmentation
We explore the task of language-guided video segmentation (LVS). Previou...
research
∙
02/18/2022
Improving Molecular Contrastive Learning via Faulty Negative Mitigation and Decomposed Fragment Contrast
Deep learning has been a prevalence in computational chemistry and widel...
research
∙
02/06/2022
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models
Recent research has shown the existence of significant redundancy in lar...
research
∙
01/09/2022
TPAD: Identifying Effective Trajectory Predictions Under the Guidance of Trajectory Anomaly Detection Model
Trajectory Prediction (TP) is an important research topic in computer vi...
research
∙
12/30/2021
A General Traffic Shaping Protocol in E-Commerce
To approach different business objectives, online traffic shaping algori...
research
∙
12/23/2021
S+PAGE: A Speaker and Position-Aware Graph Neural Network Model for Emotion Recognition in Conversation
Emotion recognition in conversation (ERC) has attracted much attention i...
research
∙
11/30/2021
AugLiChem: Data Augmentation Library of Chemical Structures for Machine Learning
Machine learning (ML) has demonstrated the promise for accurate and effi...
research
∙
11/08/2021
Creative Compensation (CC): Future of Jobs with Creative Works in 3D Printing
With the continuous growth of online 3D printing community and the democ...
research
∙
09/29/2021
Contrastive Video-Language Segmentation
We focus on the problem of segmenting a certain object referred by a nat...
research
∙
09/15/2021
Self-Training with Differentiable Teacher
Self-training achieves enormous success in various semi-supervised and w...
research
∙
09/15/2021
ARCH: Efficient Adversarial Regularized Training with Caching
Adversarial regularization can improve model generalization in many natu...
research
∙
06/02/2021
Rethinking Cross-modal Interaction from a Top-down Perspective for Referring Video Object Segmentation
Referring video object segmentation (RVOS) aims to segment video objects...
research
∙
05/25/2021
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization
The Lottery Ticket Hypothesis suggests that an over-parametrized network...
research
∙
04/21/2021
Carbon Emissions and Large Neural Network Training
The computation demand for machine learning (ML) has grown rapidly recen...
research
∙
04/11/2021
Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach
Adversarial training has been shown to improve the generalization perfor...
research
∙
03/20/2021
Token-wise Curriculum Learning for Neural Machine Translation
Existing curriculum learning approaches to Neural Machine Translation (N...
research
∙
03/19/2021
ClawCraneNet: Leveraging Object-level Relation for Text-based Video Segmentation
Text-based video segmentation is a challenging task that segments out th...
research
∙
02/24/2021
3D4ALL: Toward an Inclusive Pipeline to Classify 3D Contents
Algorithmic content moderation manages an explosive number of user-creat...
research
∙
02/03/2021
LinkLouvain: Link-Aware A/B Testing and Its Application on Online Marketing Campaign
A lot of online marketing campaigns aim to promote user interaction. The...
research
∙
01/21/2021
PyGlove: Symbolic Programming for Automated Machine Learning
Neural networks are sensitive to hyper-parameter and architecture choice...
research
∙
08/15/2020
Compositional Generalization via Neural-Symbolic Stack Machines
Despite achieving tremendous success, existing deep learning models have...
research
∙
06/28/2020
BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision
We study the open-domain named entity recognition (NER) problem under di...
research
∙
03/06/2020
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
Machine learning research has advanced in multiple aspects, including mo...
research
∙
03/05/2020
InfDetect: a Large Scale Graph-based Fraud Detection System for E-Commerce Insurance
The insurance industry has been creating innovative products around the ...
research
∙
02/27/2020
Uncovering Insurance Fraud Conspiracy with Network Learning
Fraudulent claim detection is one of the greatest challenges the insuran...
research
∙
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...
research
∙
05/03/2019
A New Hierarchical Software Architecture Towards Safety-Critical Aspects of a Drone System
In this paper, a new hierarchical software architecture is proposed to i...
research
∙
04/15/2019
Learning to Guide: Guidance Law Based on Deep Meta-learning and Model Predictive Path Integral Control
In this paper, we present a novel guidance scheme based on model-based d...
research
∙
02/19/2019
Learning to Generalize from Sparse and Underspecified Rewards
We consider the problem of learning from sparse and underspecified rewar...
research
∙
01/30/2019
