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08/11/2023
Fast and Accurate Transferability Measurement by Evaluating Intra-class Feature Variance
Given a set of pre-trained models, how can we quickly and accurately fin...
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08/07/2023
Knowledge-preserving Pruning for Pre-trained Language Models without Retraining
Given a pre-trained language model, how can we efficiently compress it w...
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05/28/2023
Fast and Accurate Dual-Way Streaming PARAFAC2 for Irregular Tensors – Algorithm and Application
How can we efficiently and accurately analyze an irregular tensor in a d...
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12/17/2022
Accurate Open-set Recognition for Memory Workload
How can we accurately identify new memory workloads while classifying kn...
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10/19/2022
Diversely Regularized Matrix Factorization for Accurate and Aggregately Diversified Recommendation
When recommending personalized top-k items to users, how can we recommen...
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08/12/2022
Accurate Action Recommendation for Smart Home via Two-Level Encoders and Commonsense Knowledge
How can we accurately recommend actions for users to control their devic...
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06/09/2022
Accurate Node Feature Estimation with Structured Variational Graph Autoencoder
Given a graph with partial observations of node features, how can we est...
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03/24/2022
DPar2: Fast and Scalable PARAFAC2 Decomposition for Irregular Dense Tensors
Given an irregular dense tensor, how can we efficiently analyze it? An i...
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02/21/2022
Model-Agnostic Augmentation for Accurate Graph Classification
Given a graph dataset, how can we augment it for accurate graph classifi...
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12/28/2020
Signed Graph Diffusion Network
Given a signed social graph, how can we learn appropriate node represent...
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12/19/2020
T-GAP: Learning to Walk across Time for Temporal Knowledge Graph Completion
Temporal knowledge graphs (TKGs) inherently reflect the transient nature...
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12/16/2020
Time-Aware Tensor Decomposition for Missing Entry Prediction
Given a time-evolving tensor with missing entries, how can we effectivel...
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09/30/2020
Pea-KD: Parameter-efficient and Accurate Knowledge Distillation
How can we efficiently compress a model while maintaining its performanc...
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09/30/2020
AUBER: Automated BERT Regularization
How can we effectively regularize BERT? Although BERT proves its effecti...
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09/29/2020
Ensemble Multi-Source Domain Adaptation with Pseudolabels
Given multiple source datasets with labels, how can we train a target mo...
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08/28/2020
Fast Partial Fourier Transform
Given a time series vector, how can we efficiently compute a specified p...
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12/23/2019
How to Pick the Best Source Data? Measuring Transferability for Heterogeneous Domains
Given a set of source data with pre-trained classification models, how c...
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09/25/2019
FALCON: Fast and Lightweight Convolution for Compressing and Accelerating CNN
How can we efficiently compress Convolutional Neural Networks (CNN) whil...
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08/22/2019
Data Context Adaptation for Accurate Recommendation with Additional Information
Given a sparse rating matrix and an auxiliary matrix of users or items, ...
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05/02/2018
Zoom-SVD: Fast and Memory Efficient Method for Extracting Key Patterns in an Arbitrary Time Range
Given multiple time series data, how can we efficiently find latent patt...
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05/02/2018
TR-SVD: Fast and Memory Efficient Method for Time Ranged Singular Value Decomposition
Given multiple time series data, how can we efficiently find latent patt...
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02/07/2018
Efficient Learning of Bounded-Treewidth Bayesian Networks from Complete and Incomplete Data Sets
Learning a Bayesian networks with bounded treewidth is important for red...
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10/18/2017
UniWalk: Explainable and Accurate Recommendation for Rating and Network Data
How can we leverage social network data and observed ratings to correctl...
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10/06/2017
Scalable Tucker Factorization for Sparse Tensors - Algorithms and Discoveries
Given sparse multi-dimensional data (e.g., (user, movie, time; rating) f...
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09/26/2017
PMV: Pre-partitioned Generalized Matrix-Vector Multiplication for Scalable Graph Mining
How can we analyze enormous networks including the Web and social networ...
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08/30/2017
A Comparative Study of Matrix Factorization and Random Walk with Restart in Recommender Systems
Between matrix factorization or Random Walk with Restart (RWR), which me...
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08/29/2017
