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08/18/2023
Rethinking Image Forgery Detection via Contrastive Learning and Unsupervised Clustering
Image forgery detection aims to detect and locate forged regions in an i...
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07/06/2023
TL-nvSRAM-CIM: Ultra-High-Density Three-Level ReRAM-Assisted Computing-in-nvSRAM with DC-Power Free Restore and Ternary MAC Operations
Accommodating all the weights on-chip for large-scale NNs remains a grea...
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05/20/2023
Dynamic Transformers Provide a False Sense of Efficiency
Despite much success in natural language processing (NLP), pre-trained l...
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05/12/2023
Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression
Communication compression is an essential strategy for alleviating commu...
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03/21/2023
Effective Ambiguity Attack Against Passport-based DNN Intellectual Property Protection Schemes through Fully Connected Layer Substitution
Since training a deep neural network (DNN) is costly, the well-trained d...
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11/23/2022
A 65nm 8b-Activation 8b-Weight SRAM-Based Charge-Domain Computing-in-Memory Macro Using A Fully-Parallel Analog Adder Network and A Single-ADC Interface
Performing data-intensive tasks in the von Neumann architecture is chall...
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10/31/2022
SEVGGNet-LSTM: a fused deep learning model for ECG classification
This paper presents a fused deep learning algorithm for ECG classificati...
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10/30/2022
Generate, Discriminate and Contrast: A Semi-Supervised Sentence Representation Learning Framework
Most sentence embedding techniques heavily rely on expensive human-annot...
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10/21/2022
Analyzing and Evaluating Faithfulness in Dialogue Summarization
Dialogue summarization is abstractive in nature, making it suffer from f...
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10/14/2022
Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization
Decentralized optimization is effective to save communication in large-s...
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08/18/2022
GRAPHIC: GatheR-And-Process in Highly parallel with In-SSD Compression Architecture in Very Large-Scale Graph
Graph convolutional network (GCN), an emerging algorithm for graph compu...
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06/08/2022
Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression
Recent advances in distributed optimization and learning have shown that...
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06/01/2022
YOLoC: DeploY Large-Scale Neural Network by ROM-based Computing-in-Memory using ResiduaL Branch on a Chip
Computing-in-memory (CiM) is a promising technique to achieve high energ...
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05/23/2022
FAST: A Fully-Concurrent Access Technique to All SRAM Rows for Enhanced Speed and Energy Efficiency in Data-Intensive Applications
Compute-in-memory (CiM) is a promising approach to improving the computi...
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11/08/2021
BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning
Decentralized algorithm is a form of computation that achieves a global ...
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10/26/2021
Exponential Graph is Provably Efficient for Decentralized Deep Training
Decentralized SGD is an emerging training method for deep learning known...
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10/05/2021
Investigating the Impact of Pre-trained Language Models on Dialog Evaluation
Recently, there is a surge of interest in applying pre-trained language ...
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10/04/2021
Revisiting Self-Training for Few-Shot Learning of Language Model
As unlabeled data carry rich task-relevant information, they are proven ...
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08/11/2021
Road Mapping and Localization using Sparse Semantic Visual Features
We present a novel method for visual mapping and localization for autono...
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07/23/2021
Bias Loss for Mobile Neural Networks
Compact convolutional neural networks (CNNs) have witnessed exceptional ...
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06/02/2021
DynaEval: Unifying Turn and Dialogue Level Evaluation
A dialogue is essentially a multi-turn interaction among interlocutors. ...
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05/19/2021
Accelerating Gossip SGD with Periodic Global Averaging
Communication overhead hinders the scalability of large-scale distribute...
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04/24/2021
DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training
The scale of deep learning nowadays calls for efficient distributed trai...
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03/26/2021
IMU Data Processing For Inertial Aided Navigation: A Recurrent Neural Network Based Approach
In this work, we propose a novel method for performing inertial aided na...
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03/16/2021
Learned Gradient Compression for Distributed Deep Learning
Training deep neural networks on large datasets containing high-dimensio...
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06/08/2020
Kinematics Based Visual Localization for Skid-Steering Robots: Algorithm and Theory
In recent years, the volume of the commercial mobile robot market has be...
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11/13/2019
Visual-Inertial Localization for Skid-Steering Robots with Kinematic Constraints
While visual localization or SLAM has witnessed great progress in past d...
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09/11/2019
A Lightweight and Accurate Localization Algorithm Using Multiple Inertial Measurement Units
In this paper, a lightweight and accurate localization algorithm is prop...
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09/08/2019
Localization for Ground Robots: On Manifold Representation, Integration, Re-Parameterization, and Optimization
In this paper, we focus on localizing ground robots, by probabilisticall...
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04/22/2019