74 citations · 96 across the 10 of their papers we have counts for
10 papers
A Seesaw Model Attack Algorithm for Distributed Learning
Kun Yang, Tianyi Luo, Yanjie Dong +1
We investigate the Byzantine attack problem within the context of model training in distributed learning systems. While ensuring the convergence of current model training processes…
To Aggregate or Not? Learning with Separate Noisy Labels
Jiaheng Wei, Zhaowei Zhu, Tianyi Luo +3
The rawly collected training data often comes with separate noisy labels collected from multiple imperfect annotators (e.g., via crowdsourcing). A typical way of using these separa…
Interpretable Research Replication Prediction via Variational Contextual Consistency Sentence Masking
Tianyi Luo, Rui Meng, Xin Eric Wang +1
Research Replication Prediction (RRP) is the task of predicting whether a published research result can be replicated or not. Building an interpretable neural text classifier for R…
Compressed Predictive Information Coding
Rui Meng, Tianyi Luo, Kristofer Bouchard
Unsupervised learning plays an important role in many fields, such as artificial intelligence, machine learning, and neuroscience. Compared to static data, methods for extracting l…
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning
Zhaowei Zhu, Tianyi Luo, Yang Liu
Semi-supervised learning (SSL) has demonstrated its potential to improve the model accuracy for a variety of learning tasks when the high-quality supervised data is severely limite…
Machine Truth Serum
Tianyi Luo, Yang Liu
Wisdom of the crowd revealed a striking fact that the majority answer from a crowd is often more accurate than any individual expert. We observed the same story in machine learning…
Can Machine Generate Traditional Chinese Poetry? A Feigenbaum Test
Qixin Wang, Tianyi Luo, Dong Wang
Recent progress in neural learning demonstrated that machines can do well in regularized tasks, e.g., the game of Go. However, artistic activities such as poem generation are still…
Chinese Song Iambics Generation with Neural Attention-based Model
Qixin Wang, Tianyi Luo, Dong Wang +1
Learning and generating Chinese poems is a charming yet challenging task. Traditional approaches involve various language modeling and machine translation techniques, however, they…
Stochastic Top-k ListNet
Tianyi Luo, Dong Wang, Rong Liu +1
ListNet is a well-known listwise learning to rank model and has gained much attention in recent years. A particular problem of ListNet, however, is the high computation complexity…
Learning from LDA using Deep Neural Networks
Dongxu Zhang, Tianyi Luo, Dong Wang +1
Latent Dirichlet Allocation (LDA) is a three-level hierarchical Bayesian model for topic inference. In spite of its great success, inferring the latent topic distribution with LDA…