7 citations · 8 across the 2 of their papers we have counts for
6 papers
Harnessing Slow Dynamics in Neuromorphic Computation
Tianlin Liu
Neuromorphic Computing is a nascent research field in which models and devices are designed to process information by emulating biological neural systems. Thanks to their superior…
Continual Learning for Sentence Representations Using Conceptors
Tianlin Liu, Lyle Ungar, João Sedoc
Distributed representations of sentences have become ubiquitous in natural language processing tasks. In this paper, we consider a continual learning scenario for sentence represen…
Unsupervised Post-processing of Word Vectors via Conceptor Negation
Tianlin Liu, Lyle Ungar, João Sedoc
Word vectors are at the core of many natural language processing tasks. Recently, there has been interest in post-processing word vectors to enrich their semantic information. In t…
Correcting the Common Discourse Bias in Linear Representation of Sentences using Conceptors
Tianlin Liu, João Sedoc, Lyle Ungar
Distributed representations of words, better known as word embeddings, have become important building blocks for natural language processing tasks. Numerous studies are devoted to…
A Consistent Method for Learning OOMs from Asymptotically Stationary Time Series Data Containing Missing Values
Tianlin Liu
In the traditional framework of spectral learning of stochastic time series models, model parameters are estimated based on trajectories of fully recorded observations. However, re…
Estimating Gradual-Emotional Behavior in One-Minute Videos with ESNs
Tianlin Liu, Arvid Kappas
In this paper, we describe our approach for the OMG- Emotion Challenge 2018. The goal is to produce utterance-level valence and arousal estimations for videos of approximately 1 mi…