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06/02/2022
Invertible Neural Networks for Graph Prediction
In this work, we address conditional generation using deep invertible ne...
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05/16/2022
Transfer learning based physics-informed neural networks for solving inverse problems in tunneling
Recently, a class of machine learning methods called physics-informed ne...
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05/02/2022
COSPLAY: Concept Set Guided Personalized Dialogue Generation Across Both Party Personas
Maintaining a consistent persona is essential for building a human-like ...
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03/06/2022
Learnable Irrelevant Modality Dropout for Multimodal Action Recognition on Modality-Specific Annotated Videos
With the assumption that a video dataset is multimodality annotated in w...
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02/17/2022
Training neural networks using monotone variational inequality
Despite the vast empirical success of neural networks, theoretical under...
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01/10/2022
SMLE: An R Package for Joint Feature Screening in Ultrahigh-dimensional GLMs
The sparsity-restricted maximum likelihood estimator (SMLE) has received...
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08/09/2021
A Credibility-aware Swarm-Federated Deep Learning Framework in Internet of Vehicles
Federated Deep Learning (FDL) is helping to realize distributed machine ...
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07/06/2021
The NiuTrans End-to-End Speech Translation System for IWSLT 2021 Offline Task
This paper describes the submission of the NiuTrans end-to-end speech tr...
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06/26/2021
A new mathematical model for dispersion of Rayleigh wave and a machine learning based inversion solver
In this work, by introducing the seismic impedance tensor we propose a n...
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05/25/2021
Conformal Anomaly Detection on Spatio-Temporal Observations with Missing Data
We develop a distribution-free, unsupervised anomaly detection method ca...
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05/12/2021
Stacked Acoustic-and-Textual Encoding: Integrating the Pre-trained Models into Speech Translation Encoders
Encoder pre-training is promising in end-to-end Speech Translation (ST),...
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04/30/2021
DPR-CAE: Capsule Autoencoder with Dynamic Part Representation for Image Parsing
Parsing an image into a hierarchy of objects, parts, and relations is im...
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04/21/2021
Stable Nonlinear and IQ Imbalance RF Fingerprint for Wireless OFDM Devices
An estimation method of Radio Frequency fingerprint (RFF) based on the p...
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03/22/2021
Smart Scheduling based on Deep Reinforcement Learning for Cellular Networks
To improve the system performance towards the Shannon limit, advanced ra...
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01/27/2021
Solar Radiation Anomaly Events Modeling Using Spatial-Temporal Mutually Interactive Processes
Modeling and predicting solar events, in particular, the solar ramping e...
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01/06/2021
HAVANA: Hierarchical and Variation-Normalized Autoencoder for Person Re-identification
Person Re-Identification (Re-ID) is of great importance to the many vide...
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11/30/2020
Dynamic Curriculum Learning for Low-Resource Neural Machine Translation
Large amounts of data has made neural machine translation (NMT) a big su...
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10/18/2020
Conformal prediction interval for dynamic time-series
We develop a method to build distribution-free prediction intervals in b...
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10/15/2020
Wasserstein Distance Regularized Sequence Representation for Text Matching in Asymmetrical Domains
One approach to matching texts from asymmetrical domains is projecting t...
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06/06/2020
MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal Angles
The strong correlation between neurons or filters can significantly weak...
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02/20/2020
Predictive Inference Is Free with the Jackknife+-after-Bootstrap
Ensemble learning is widely used in applications to make predictions in ...
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02/18/2020
Multiplicative Noise Removal: Nonlocal Low-Rank Model and Its Proximal Alternating Reweighted Minimization Algorithm
The goal of this paper is to develop a novel numerical method for effici...
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12/03/2019
SAIS: Single-stage Anchor-free Instance Segmentation
In this paper, we propose a simple yet efficientinstance segmentation ap...
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11/13/2019
Buffer-aware Wireless Scheduling based on Deep Reinforcement Learning
In this paper, the downlink packet scheduling problem for cellular netwo...
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07/22/2019
Realistic Channel Models Pre-training
In this paper, we propose a neural-network-based realistic channel model...
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07/11/2019
Privileged Features Distillation for E-Commerce Recommendations
Features play an important role in most prediction tasks of e-commerce r...
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05/15/2019
Deep Reinforcement Learning for Scheduling in Cellular Networks
Integrating artificial intelligence (AI) into wireless networks has draw...
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04/30/2019
PR Product: A Substitute for Inner Product in Neural Networks
In this paper, we analyze the inner product of weight vector and input v...
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03/09/2019
Distributed Feature Screening via Componentwise Debiasing
Feature screening is a powerful tool in the analysis of high dimensional...
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01/14/2019
Predicting the Mumble of Wireless Channel with Sequence-to-Sequence Models
Accurate prediction of fading channel in future is essential to realize ...
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08/06/2018
A Flip-Syndrome-List Polar Decoder Architecture for Ultra-Low-Latency Communications
We consider practical hardware implementation of Polar decoders. To redu...
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02/01/2018
Alternating Multi-bit Quantization for Recurrent Neural Networks
Recurrent neural networks have achieved excellent performance in many ap...
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05/05/2015
On the Feasibility of Distributed Kernel Regression for Big Data
In modern scientific research, massive datasets with huge numbers of obs...
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07/25/2013