LEMMA
74 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in LEMMA
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Most implemented papers
Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning
In this paper, we extend the theory of trust region learning to MARL.
UniMorph 2.0: Universal Morphology
The Universal Morphology UniMorph project is a collaborative effort to improve how NLP handles complex morphology across the world's languages.
Deep Generation of Coq Lemma Names Using Elaborated Terms
Our results show that Roosterize substantially outperforms baselines for suggesting lemma names, highlighting the importance of using multi-input models and elaborated terms.
Morphological analysis using a sequence decoder
Our Morse implementation and the TrMor2018 dataset are available online to support future research\footnote{See \url{https://github. com/ai-ku/Morse. jl} for a Morse implementation in Julia/Knet \cite{knet2016mlsys} and \url{https://github. com/ai-ku/TrMor2018} for the new Turkish dataset.
Improving Lemmatization of Non-Standard Languages with Joint Learning
Lemmatization of standard languages is concerned with (i) abstracting over morphological differences and (ii) resolving token-lemma ambiguities of inflected words in order to map them to a dictionary headword.
Deterministic tensor completion with hypergraph expanders
We provide a novel analysis of low-rank tensor completion based on hypergraph expanders.
Generalizing to unseen domains via distribution matching
In this work, we tackle such problem by focusing on domain generalization: a formalization where the data generating process at test time may yield samples from never-before-seen domains (distributions).
On the distance between two neural networks and the stability of learning
This paper relates parameter distance to gradient breakdown for a broad class of nonlinear compositional functions.
Post-selection inference with HSIC-Lasso
Detecting influential features in non-linear and/or high-dimensional data is a challenging and increasingly important task in machine learning.
Adaptive Data-Driven Prediction in a Building Control Hierarchy: A Case Study of Demand Response in Switzerland
By providing various services, such as Demand Response (DR), buildings can play a crucial role in the energy market due to their significant energy consumption.