Search Results for author:
Found 8 papers, 3 papers with code
Integrated Triaging for Fast Reading Comprehension
This paper introduces Integrated Triaging, a framework that prunes almost all context in early layers of a network, leaving the remaining (deep) layers to scan only a tiny fraction of the full corpus.
FastFusionNet: New State-of-the-Art for DAWNBench SQuAD
In this technical report, we introduce FastFusionNet, an efficient variant of FusionNet [12].
Fast Reading Comprehension with ConvNets
State-of-the-art deep reading comprehension models are dominated by recurrent neural nets.
Evaluating Induced CCG Parsers on Grounded Semantic Parsing
We compare the effectiveness of four different syntactic CCG parsers for a semantic slot-filling task to explore how much syntactic supervision is required for downstream semantic analysis.
Co-Training for Domain Adaptation
Our algorithm is a variant of co-training, and we name it CODA (Co-training for domain adaptation).
Regularized Learning with Networks of Features
Here we present a framework for regularized learning in settings where one has prior knowledge about which features are expected to have similar and dissimilar weights.
Learning Bounds for Domain Adaptation
Empirical risk minimization offers well-known learning guarantees when training and test data come from the same domain.
Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification
Automatic sentiment classification has been extensively studied and applied in recent years.
