537 citations · 584 across the 9 of their papers we have counts for
9 papers
Overlooked Poses Actually Make Sense: Distilling Privileged Knowledge for Human Motion Prediction
Xiaoning Sun, Qiongjie Cui, Huaijiang Sun +3
Previous works on human motion prediction follow the pattern of building a mapping relation between the sequence observed and the one to be predicted. However, due to the inherent…
One-dimensional Tensor Network Recovery
Ziang Chen, Jianfeng Lu, Anru R. Zhang
We study the recovery of the underlying graphs or permutations for tensors in the tensor ring or tensor train format. Our proposed algorithms compare the matricization ranks after…
Stable Phase Retrieval from Locally Stable and Conditionally Connected Measurements
Cheng Cheng, Ingrid Daubechies, Nadav Dym +1
This paper is concerned with stable phase retrieval for a family of phase retrieval models we name "locally stable and conditionally connected" (LSCC) measurement schemes. For ever…
LightPAFF: A Two-Stage Distillation Framework for Pre-training and Fine-tuning
Kaitao Song, Hao Sun, Xu Tan +4
While pre-training and fine-tuning, e.g., BERT~\citep{devlin2018bert}, GPT-2~\citep{radford2019language}, have achieved great success in language understanding and generation tasks…
MPNet: Masked and Permuted Pre-training for Language Understanding
Kaitao Song, Xu Tan, Tao Qin +2
BERT adopts masked language modeling (MLM) for pre-training and is one of the most successful pre-training models. Since BERT neglects dependency among predicted tokens, XLNet intr…
Non-Convex Planar Harmonic Maps
Shahar Z. Kovalsky, Noam Aigerman, Ingrid Daubechies +3
We formulate a novel characterization of a family of invertible maps between two-dimensional domains. Our work follows two classic results: The Radó-Kneser-Choquet (RKC) theorem, w…
Hybrid Self-Attention Network for Machine Translation
Kaitao Song, Xu Tan, Furong Peng +1
The encoder-decoder is the typical framework for Neural Machine Translation (NMT), and different structures have been developed for improving the translation performance. Transform…
Stop memorizing: A data-dependent regularization framework for intrinsic pattern learning
Wei Zhu, Qiang Qiu, Bao Wang +3
Deep neural networks (DNNs) typically have enough capacity to fit random data by brute force even when conventional data-dependent regularizations focusing on the geometry of the f…
Synchrosqueezed Wavelet Transforms: a Tool for Empirical Mode Decomposition
Ingrid Daubechies, Jianfeng Lu, Hau-Tieng Wu
The EMD algorithm, first proposed in [11], made more robust as well as more versatile in [12], is a technique that aims to decompose into their building blocks functions that are t…