Hongxia Jin
Artificial Intelligence · 2013–2022
A researcher in the Science corpus: 19 papers; trusts 778 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 302 citations into it; #11,535 of 35,345 by trust here, #6,569 by citations
- Computer Vision and Pattern Recognition — 186 citations into it; #9,261 of 21,575 by trust here, #6,089 by citations
- Natural Language Processing — 81 citations into it; #3,469 of 5,688 by trust here, #5,092 by citations
- Sociology and Political Science — 37 citations into it
- Efficiency & Compression — 35 citations into it
- Privacy & Security — 33 citations into it
- Meta & Continual Learning — 31 citations into it; #646 of 1,041 by trust here, #568 by citations
- Representation & Self-Supervised Learning — 31 citations into it
Whom Hongxia Jin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Kaiming He
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Yann LeCun
- David G. Lowe
- Oriol Vinyals
- Ross B. Girshick
Who trusts Hongxia Jin overall
Papers from Hongxia Jin's perspective
Ordered by how strongly the researchers Hongxia Jin trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded (2019) — 299 citations
- Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning (2021) — 213 citations
- Generalized ODIN: Detecting Out-of-Distribution Image Without Learning From Out-of-Distribution Data (2020) — 700 citations
- Negative Data Augmentation (2021) — 83 citations
- Private spatial data aggregation in the local setting (2016) — 177 citations
- Language model compression with weighted low-rank factorization (2022) — 241 citations
- Automatic Mixed-Precision Quantization Search of BERT (2021) — 26 citations
- Iterative Delexicalization for Improved Spoken Language Understanding (2019) — 8 citations
- A Progressive Model to Enable Continual Learning for Semantic Slot Filling (2019) — 36 citations
- Adversarial Multi-label Prediction for Spoken and Visual Signal Tagging (2019)
- SLiQA-I: Towards Cold-start Development of End-to-end Spoken Language Interface for Question Answering (2019) — 8 citations
- CRUISE: Cold-Start New Skill Development via Iterative Utterance Generation (2018) — 9 citations
- Learning Out-of-Vocabulary Words in Intelligent Personal Agents (2018) — 7 citations
- User Information Augmented Semantic Frame Parsing Using Progressive Neural Networks (2018) — 7 citations
- A Bi-Model Based RNN Semantic Frame Parsing Model for Intent Detection and Slot Filling (2018) — 216 citations
- Privacy-CNH: A Framework to Detect Photo Privacy with Convolutional Neural Network using Hierarchical Features (2016) — 78 citations
- Generalizing DTW to the multi-dimensional case requires an adaptive approach (2016) — 322 citations
- Differentially Private K-Means Clustering (2015) — 169 citations
- Counteracting the Negative Effect of Form Auto-completion on the Privacy Calculus (2013) — 40 citations