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08/26/2023
Semi-Supervised Semantic Segmentation via Marginal Contextual Information
We present a novel confidence refinement scheme that enhances pseudo-lab...
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05/22/2023
Enhanced Meta Label Correction for Coping with Label Corruption
Traditional methods for learning with the presence of noisy labels have ...
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03/27/2023
Classifier Robustness Enhancement Via Test-Time Transformation
It has been recently discovered that adversarially trained classifiers e...
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07/11/2022
Physical Passive Patch Adversarial Attacks on Visual Odometry Systems
Deep neural networks are known to be susceptible to adversarial perturba...
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06/13/2022
GoToNet: Fast Monocular Scene Exposure and Exploration
Autonomous scene exposure and exploration, especially in localization or...
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05/31/2022
Strategic Classification with Graph Neural Networks
Strategic classification studies learning in settings where users can mo...
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05/30/2022
FBM: Fast-Bit Allocation for Mixed-Precision Quantization
Quantized neural networks are well known for reducing latency, power con...
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04/05/2022
Bimodal Distributed Binarized Neural Networks
Binary Neural Networks (BNNs) are an extremely promising method to reduc...
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03/02/2022
A Simple and Universal Rotation Equivariant Point-cloud Network
Equivariance to permutations and rigid motions is an important inductive...
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01/31/2022
Weisfeiler and Leman Go Infinite: Spectral and Combinatorial Pre-Colorings
Graph isomorphism testing is usually approached via the comparison of gr...
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01/30/2022
On Recoverability of Graph Neural Network Representations
Despite their growing popularity, graph neural networks (GNNs) still hav...
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11/29/2021
End-to-End Referring Video Object Segmentation with Multimodal Transformers
The referring video object segmentation task (RVOS) involves segmentatio...
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03/25/2021
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels
The success of learning with noisy labels (LNL) methods relies heavily o...
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03/22/2021
Intersection Regularization for Extracting Semantic Attributes
We consider the problem of supervised classification, such that the feat...
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11/06/2020
Single-Node Attack for Fooling Graph Neural Networks
Graph neural networks (GNNs) have shown broad applicability in a variety...
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08/24/2020
Self-Supervised Learning for Large-Scale Unsupervised Image Clustering
Unsupervised learning has always been appealing to machine learning rese...
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04/19/2020
HCM: Hardware-Aware Complexity Metric for Neural Network Architectures
Convolutional Neural Networks (CNNs) have become common in many fields i...
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03/04/2020
Colored Noise Injection for Training Adversarially Robust Neural Networks
Even though deep learning have shown unmatched performance on various ta...
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11/17/2019
Smoothed Inference for Adversarially-Trained Models
Deep neural networks are known to be vulnerable to inputs with malicious...
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11/17/2019
Loss Aware Post-training Quantization
Neural network quantization enables the deployment of large models on re...
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09/25/2019
CAT: Compression-Aware Training for bandwidth reduction
Convolutional neural networks (CNNs) have become the dominant neural net...
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05/26/2019
Feature Map Transform Coding for Energy-Efficient CNN Inference
Convolutional neural networks (CNNs) achieve state-of-the-art accuracy i...
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04/22/2019
Towards Learning of Filter-Level Heterogeneous Compression of Convolutional Neural Networks
Recently, deep learning has become a de facto standard in machine learni...
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02/07/2019
Beholder-GAN: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level
Beauty is in the eye of the beholder. This maxim, emphasizing the subjec...
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11/27/2018
Efficient non-uniform quantizer for quantized neural network targeting reconfigurable hardware
Convolutional Neural Networks (CNN) has become more popular choice for v...
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09/29/2018
NICE: Noise Injection and Clamping Estimation for Neural Network Quantization
Convolutional Neural Networks (CNN) are very popular in many fields incl...
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04/29/2018
UNIQ: Uniform Noise Injection for non-uniform Quantization of neural networks
We present a novel method for training a neural network amenable to infe...
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04/29/2018
UNIQ: Uniform Noise Injection for the Quantization of Neural Networks
We present a novel method for training deep neural network amenable to i...
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07/31/2017
