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05/31/2023
Integrated multi-operand optical neurons for scalable and hardware-efficient deep learning
The optical neural network (ONN) is a promising hardware platform for ne...
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05/31/2023
DOTA: A Dynamically-Operated Photonic Tensor Core for Energy-Efficient Transformer Accelerator
The wide adoption and significant computing resource consumption of atte...
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05/31/2023
M3ICRO: Machine Learning-Enabled Compact Photonic Tensor Core based on PRogrammable Multi-Operand Multimode Interference
Photonic computing shows promise for transformative advancements in mach...
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05/24/2023
Pre-RMSNorm and Pre-CRMSNorm Transformers: Equivalent and Efficient Pre-LN Transformers
Transformers have achieved great success in machine learning application...
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11/30/2022
HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression
Transformers have attained superior performance in natural language proc...
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10/30/2022
QuEst: Graph Transformer for Quantum Circuit Reliability Estimation
Among different quantum algorithms, PQC for QML show promises on near-te...
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09/19/2022
NeurOLight: A Physics-Agnostic Neural Operator Enabling Parametric Photonic Device Simulation
Optical computing is an emerging technology for next-generation efficien...
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08/17/2022
Fuse and Mix: MACAM-Enabled Analog Activation for Energy-Efficient Neural Acceleration
Analog computing has been recognized as a promising low-power alternativ...
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07/30/2022
Delving into Effective Gradient Matching for Dataset Condensation
As deep learning models and datasets rapidly scale up, network training ...
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07/13/2022
RobustAnalog: Fast Variation-Aware Analog Circuit Design Via Multi-task RL
Analog/mixed-signal circuit design is one of the most complex and time-c...
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06/02/2022
Universal Polar Coding for Parallel Gaussian Channels with Non-Binary Inputs and Its Applications to HARQ and MIMO
In this paper, we first propose an universal polar coding scheme for par...
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04/02/2022
Homography Loss for Monocular 3D Object Detection
Monocular 3D object detection is an essential task in autonomous driving...
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03/13/2022
CVFNet: Real-time 3D Object Detection by Learning Cross View Features
In recent years 3D object detection from LiDAR point clouds has made gre...
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02/26/2022
QOC: Quantum On-Chip Training with Parameter Shift and Gradient Pruning
Parameterized Quantum Circuits (PQC) are drawing increasing research int...
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12/15/2021
ELight: Enabling Efficient Photonic In-Memory Neurocomputing with Life Enhancement
With the recent advances in optical phase change material (PCM), photoni...
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11/11/2021
Silicon photonic subspace neural chip for hardware-efficient deep learning
As deep learning has shown revolutionary performance in many artificial ...
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11/01/2021
HRViT: Multi-Scale High-Resolution Vision Transformer
Vision transformers (ViTs) have attracted much attention for their super...
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10/27/2021
L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization
Silicon-photonics-based optical neural network (ONN) is a promising hard...
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10/21/2021
RoQNN: Noise-Aware Training for Robust Quantum Neural Networks
Quantum Neural Network (QNN) is a promising application towards quantum ...
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10/04/2021
A New Acceleration Paradigm for Discrete CosineTransform and Other Fourier-Related Transforms
Discrete cosine transform (DCT) and other Fourier-related transforms hav...
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08/28/2021
DenseLiDAR: A Real-Time Pseudo Dense Depth Guided Depth Completion Network
Depth Completion can produce a dense depth map from a sparse input and p...
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08/25/2021
Towards Memory-Efficient Neural Networks via Multi-Level in situ Generation
Deep neural networks (DNN) have shown superior performance in a variety ...
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07/22/2021
QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits
Quantum noise is the key challenge in Noisy Intermediate-Scale Quantum (...
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04/15/2021
Performance of CRC Concatenated Pre-transformed RM-Polar Codes
In this paper, we discuss pre-transformed RM-Polar codes and cyclic redu...
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04/01/2021
Optimizer Fusion: Efficient Training with Better Locality and Parallelism
Machine learning frameworks adopt iterative optimizers to train neural n...
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02/10/2021
Bayesian Knockoff Filter Using Gibbs Sampler
In many fields, researchers are interested in discovering features with ...
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12/21/2020
Efficient On-Chip Learning for Optical Neural Networks Through Power-Aware Sparse Zeroth-Order Optimization
Optical neural networks (ONNs) have demonstrated record-breaking potenti...
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11/20/2020
Reconstruct Kaplan–Meier Estimator as M-estimator and Its Confidence Band
The Kaplan–Meier (KM) estimator, which provides a nonparametric estimate...
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12/13/2019
On Pre-transformed Polar Codes
In this paper, we prove that any pre-transformation with an upper-triang...
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10/20/2019
