8 citations · 21 across the 11 of their papers we have counts for
4 papers · 1 filter
Universal Approximation Under Constraints is Possible with Transformers
Anastasis Kratsios, Behnoosh Zamanlooy, Tianlin Liu +1
Many practical problems need the output of a machine learning model to satisfy a set of constraints, . Nevertheless, there is no known guarantee that classical neural network ar…
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…
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…