Deep Learning
Image Captioning: Transforming Objects into Words
Simao Herdade, Armin Kappeler, Kofi Boakye, Joao Soares
One of the most successful algorithms uses feature vectors extracted from the region proposals obtained from anobject detector.
Complexity Matters: Rethinking the Latent Space for Generative Modeling
Our investigation starts with the classic generative adversarial networks (GANs). Inspired by the GAN training objective, we propose a novel "distance" between the latent and data distributions, whose minimization
Can SGD Learn Recurrent Neural Networks with Provable Generalization?
Neural Information Processing Systems http://nips.cc/
Supplementary Material for Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains 1 RansomwareDataset 1.1 BitcoinHeist features
Aou(n), where an output address au receives Aou(n) coins. On the Bitcoin network, an address may appear multiple times with different inputs and outputs. An address u that appears in a transaction at time t can be denoted as atu. Thenumberofblocksmeasuresthe speed in the 24-hour window that contains a transaction involving the coin. Second, temporal information of transactions, such as the local time, has been useful to cluster criminal transactions.
Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization
Yizhe Zhang, Michel Galley, Jianfeng Gao, Zhe Gan, Xiujun Li, Chris Brockett, Bill Dolan
We argue that this problem is in fact twofold.
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting
Shiyang Li, Xiaoyong Jin, Yao Xuan, Xiyou Zhou, Wenhu Chen, Yu-Xiang Wang, Xifeng Yan
Neural Information Processing Systems http://nips.cc/