Search Results for author: Robert C. Qiu

Found 16 papers, 4 papers with code

"Lossless" Compression of Deep Neural Networks: A High-dimensional Neural Tangent Kernel Approach

1 code implementation1 Mar 2024 Lingyu Gu, Yongqi Du, Yuan Zhang, Di Xie, ShiLiang Pu, Robert C. Qiu, Zhenyu Liao

Modern deep neural networks (DNNs) are extremely powerful; however, this comes at the price of increased depth and having more parameters per layer, making their training and inference more computationally challenging.

Model Compression Quantization

Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures

1 code implementation5 Feb 2024 Zenan Ling, Longbo Li, Zhanbo Feng, Yixuan Zhang, Feng Zhou, Robert C. Qiu, Zhenyu Liao

Deep equilibrium models (DEQs), as a typical implicit neural network, have demonstrated remarkable success on various tasks.

DeLR: Active Learning for Detection with Decoupled Localization and Recognition Query

no code implementations28 Dec 2023 Yuhang Zhang, Yuang Deng, Xiaopeng Zhang, Jie Li, Robert C. Qiu, Qi Tian

In DeLR, the query is based on region-level, and we only annotate the object region that is queried; 2) Instead of directly providing both localization and recognition annotations, we separately query the two components, and thus reduce the recognition budget with the pseudo class labels provided by the model.

Active Learning Object +2

RIS-aided Real-time Beam Tracking for a Mobile User via Bayesian Optimization

no code implementations29 Oct 2023 Junshuo Liu, Rujing Xiong, Jialong Lu, Tiebin Mi, Robert C. Qiu

The conventional beam management procedure mandates that the user equipment (UE) periodically measure the received signal reference power (RSRP) and transmit these measurements to the base station (BS).

Bayesian Optimization Management

Timestamp-supervised Wearable-based Activity Segmentation and Recognition with Contrastive Learning and Order-Preserving Optimal Transport

no code implementations13 Oct 2023 Songpengcheng Xia, Lei Chu, Ling Pei, Jiarui Yang, Wenxian Yu, Robert C. Qiu

To address these challenges, we propose a novel method for joint activity segmentation and recognition with timestamp supervision, in which only a single annotated sample is needed in each activity segment.

Contrastive Learning Human Activity Recognition +1

Zero-shot Inversion Process for Image Attribute Editing with Diffusion Models

no code implementations30 Aug 2023 Zhanbo Feng, Zenan Ling, Ci Gong, Feng Zhou, Jie Li, Robert C. Qiu

Existing works tend to use either image-guided methods, which provide a visual reference but lack control over semantic coherence, or text-guided methods, which ensure faithfulness to text guidance but lack visual quality.

Attribute Denoising

Multi-level Contrast Network for Wearables-based Joint Activity Segmentation and Recognition

no code implementations16 Aug 2022 Songpengcheng Xia, Lei Chu, Ling Pei, Wenxian Yu, Robert C. Qiu

Human activity recognition (HAR) with wearables is promising research that can be widely adopted in many smart healthcare applications.

Activity Prediction Human Activity Recognition +1

Learning Efficient Representations for Enhanced Object Detection on Large-scene SAR Images

no code implementations22 Jan 2022 Siyan Li, Yue Xiao, Yuhang Zhang, Lei Chu, Robert C. Qiu

It is a challenging problem to detect and recognize targets on complex large-scene Synthetic Aperture Radar (SAR) images.

object-detection Object Detection

One-Bit Active Query With Contrastive Pairs

no code implementations CVPR 2022 Yuhang Zhang, Xiaopeng Zhang, Lingxi Xie, Jie Li, Robert C. Qiu, Hengtong Hu, Qi Tian

The Yes query is treated as positive pairs of the queried category for contrastive pulling, while the No query is treated as hard negative pairs for contrastive repelling.

Active Learning Contrastive Learning

Explaining AlphaGo: Interpreting Contextual Effects in Neural Networks

no code implementations8 Jan 2019 Zenan Ling, Haotian Ma, Yu Yang, Robert C. Qiu, Song-Chun Zhu, Quanshi Zhang

In this paper, we propose to disentangle and interpret contextual effects that are encoded in a pre-trained deep neural network.

A Survey on Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning

1 code implementation16 Aug 2018 Fei Wen, Lei Chu, Peilin Liu, Robert C. Qiu

In recent, nonconvex regularization based sparse and low-rank recovery is of considerable interest and it in fact is a main driver of the recent progress in nonconvex and nonsmooth optimization.

BIG-bench Machine Learning Compressive Sensing +2

Spectrum concentration in deep residual learning: a free probability approach

no code implementations31 Jul 2018 Zenan Ling, Xing He, Robert C. Qiu

We revisit the initialization of deep residual networks (ResNets) by introducing a novel analytical tool in free probability to the community of deep learning.

Positive Definite Estimation of Large Covariance Matrix Using Generalized Nonconvex Penalties

1 code implementation15 Apr 2016 Fei Wen, Yuan Yang, Peilin Liu, Robert C. Qiu

Further, the statistical properties of the new estimators have been analyzed for generalized nonconvex penalties.


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