Da-Cheng Juan | DeepAI

AI Chat

Featured Co-authors

Xin Wang
382 publications
Wei Wei
156 publications
Jia Li
149 publications
Cho-Jui Hsieh
147 publications
Ce Zhang
133 publications
Christopher Ré
125 publications
Shuai Zhang
100 publications
Yiyu Shi
93 publications
Yi Tay
76 publications
Liu Yang
73 publications
Min Sun
65 publications

∙ 07/10/2023

Substance or Style: What Does Your Image Embedding Know?

Probes are small networks that predict properties of underlying data fro...

0 Cyrus Rashtchian, et al. ∙

∙ 04/23/2023

LayerNAS: Neural Architecture Search in Polynomial Complexity

Neural Architecture Search (NAS) has become a popular method for discove...

0 Yicheng Fan, et al. ∙

∙ 10/17/2022

RARR: Researching and Revising What Language Models Say, Using Language Models

Language models (LMs) now excel at many tasks such as few-shot learning,...

0 Luyu Gao, et al. ∙

∙ 09/04/2022

Representative Image Feature Extraction via Contrastive Learning Pretraining for Chest X-ray Report Generation

Medical report generation is a challenging task since it is time-consumi...

0 Yu-Jen Chen, et al. ∙

∙ 12/14/2021

Meta-CPR: Generalize to Unseen Large Number of Agents with Communication Pattern Recognition Module

Designing an effective communication mechanism among agents in reinforce...

0 Wei-Cheng Tseng, et al. ∙

∙ 07/06/2021

Uncertainty Modeling of Emerging Device-based Computing-in-Memory Neural Accelerators with Application to Neural Architecture Search

Emerging device-based Computing-in-memory (CiM) has been proved to be a ...

0 Zheyu Yan, et al. ∙

∙ 03/01/2021

OmniNet: Omnidirectional Representations from Transformers

This paper proposes Omnidirectional Representations from Transformers (O...

19 Yi Tay, et al. ∙

∙ 02/17/2021

Switch Spaces: Learning Product Spaces with Sparse Gating

Learning embedding spaces of suitable geometry is critical for represent...

6 Shuai Zhang, et al. ∙

∙ 12/22/2020

Graph Autoencoders with Deconvolutional Networks

Recent studies have indicated that Graph Convolutional Networks (GCNs) a...

0 Jia Li, et al. ∙

∙ 12/01/2020

Adversarial Robustness Across Representation Spaces

Adversarial robustness corresponds to the susceptibility of deep neural ...

0 Pranjal Awasthi, et al. ∙

∙ 07/12/2020

HyperGrid: Efficient Multi-Task Transformers with Grid-wise Decomposable Hyper Projections

Achieving state-of-the-art performance on natural language understanding...

0 Yi Tay, et al. ∙

∙ 07/08/2020

Remix: Rebalanced Mixup

Deep image classifiers often perform poorly when training data are heavi...

2 Hsin-Ping Chou, et al. ∙

∙ 07/07/2020

Calibrated BatchNorm: Improving Robustness Against Noisy Weights in Neural Networks

Analog computing hardware has gradually received more attention by the r...

16 Li-Huang Tsai, et al. ∙

∙ 05/02/2020

Synthesizer: Rethinking Self-Attention in Transformer Models

The dot product self-attention is known to be central and indispensable ...

0 Yi Tay, et al. ∙

∙ 05/01/2020

Low-Dimensional Hyperbolic Knowledge Graph Embeddings

Knowledge graph (KG) embeddings learn low-dimensional representations of...

11 Ines Chami, et al. ∙

∙ 02/26/2020

Sparse Sinkhorn Attention

We propose Sparse Sinkhorn Attention, a new efficient and sparse method ...

0 Yi Tay, et al. ∙

∙ 11/17/2019

Learning with Hierarchical Complement Objective

Label hierarchies widely exist in many vision-related problems, ranging ...

0 Hao-Yun Chen, et al. ∙

∙ 09/06/2019

Natural Adversarial Sentence Generation with Gradient-based Perturbation

This work proposes a novel algorithm to generate natural language advers...

0 Yu-Lun Hsieh, et al. ∙

∙ 03/30/2019

COCO-GAN: Generation by Parts via Conditional Coordinating

Humans can only interact with part of the surrounding environment due to...

0 Chieh Hubert Lin, et al. ∙

∙ 03/23/2019

Improving Adversarial Robustness via Guided Complement Entropy

Model robustness has been an important issue, since adding small adversa...

0 Hao-Yun Chen, et al. ∙

∙ 03/04/2019

Complement Objective Training

Learning with a primary objective, such as softmax cross entropy for cla...

0 Hao-Yun Chen, et al. ∙

∙ 11/26/2018

InstaNAS: Instance-aware Neural Architecture Search

Neural Architecture Search (NAS) aims at finding one "single" architectu...

0 An-Chieh Cheng, et al. ∙

∙ 08/29/2018

Searching Toward Pareto-Optimal Device-Aware Neural Architectures

Recent breakthroughs in Neural Architectural Search (NAS) have achieved ...

0 An-Chieh Cheng, et al. ∙

∙ 08/22/2018

Escaping from Collapsing Modes in a Constrained Space

Generative adversarial networks (GANs) often suffer from unpredictable m...

0 Chia-Che Chang, et al. ∙

∙ 06/27/2018

MONAS: Multi-Objective Neural Architecture Search using Reinforcement Learning

Recent studies on neural architecture search have shown that automatical...

0 Chi-Hung Hsu, et al. ∙

∙ 06/21/2018

DPP-Net: Device-aware Progressive Search for Pareto-optimal Neural Architectures

Recent breakthroughs in Neural Architectural Search (NAS) have achieved ...

0 Jin-Dong Dong, et al. ∙

∙ 10/15/2017

NeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks

"How much energy is consumed for an inference made by a convolutional ne...

0 Ermao Cai, et al. ∙

∙ 08/14/2017

DC-Prophet: Predicting Catastrophic Machine Failures in DataCenters

When will a server fail catastrophically in an industrial datacenter? Is...

0 You-Luen Lee, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world