SZTAKI HLT | Seminar

Upcoming seminar

Verb sense induction with tensor decomposition
Márton Makrai
March 22, 2019, 14:00
SZTAKI, Lágymányosi u. 11.

I submitted a paper to ACL main conf with the following abstract, and plan to submit it to workshops as well. The main question of the work in progress talk is now how to evaluate the decomposition quantitatively.

We present verb representations based on dependency relations and tensor-decomposition applying the rather recent Orth-ALS decomposition algorithm to a subject × preverb × verb × object tensor in Hungarian, where preverbs (verb-modifying particles) interfere with argument structure and polisemy. The work-in-progress paper evaluates the obtained representations qualitatively, by clustering the verb embedding vectors, and showing some which intuitively fit to some semantic verb class.

Past seminars

Feb. 27, 2019 UMAP continued Gábor Borbély
Feb. 1, 2019 UMAP Gábor Borbély
Dec. 7, 2018 Deep contextualized word representations Gábor Berend
Oct. 26, 2018 Approaches to Surface Realization of Universal Dependencies Gábor Recski
Oct. 19, 2018 The Book of Why Péter Földiák
Oct. 12, 2018 Borbély: Wasserstein VAE, Makrai: mondatklaszterezés Gábor Borbély
Sept. 28, 2018 Making chatbots better by entropy-based data filtering (and future directions) Richárd Csáky
Sept. 21, 2018 SkipGram - Zipf + Uniform = Vector Additivity Gábor Borbély
Aug. 22, 2018 Expanding Access to Language through Data-Driven Design Danielle Bragg
April 13, 2018 Semantic compression and rate distortion theory for memory representations Dávid Gergely Nagy
Feb. 9, 2018 Bayesian model comparison of distributions with unequal supports Gábor Borbély
Dec. 14, 2017 Comprehensive Conditioning of Neural Conversational Models Richárd Csáky
Nov. 30, 2017 Bayesian model selection, inference and Minimum Description Length Péter Földiák
Nov. 23, 2017 Hungarian morphological segmentation using recurrent and convolutional networks Judit Ács
Nov. 9, 2017 The length of natural sentences Gábor Borbély
Nov. 2, 2017 Brainstorming for SemEval Task 10: Capturing Discriminative Attributes Márton Makrai
Sept. 21, 2017 Recurrent dropout Dávid Márk Nemeskey
Sept. 14, 2017 Stanford’s Graph-based Neural Dependency Parser Gábor Recski
Sept. 7, 2017 Chatbots Gábor Recski
June 15, 2017 Sparse Coding of Neural Word Embeddings for Multilingual Sequence Labeling Márton Makrai
June 1, 2017 Wasserstein GAN Gábor Borbély
May 11, 2017 Autoencoder experiments on Hungarian words Judit Ács
April 27, 2017 Beyond RNN: multi-dimensional RNN, RNN transducers, RNN grammars Dávid Márk Nemeskey
April 13, 2017 Training a Universal Word Embedding Eszter Iklódi
March 30, 2017 Interpreted Regular Tree Grammars for semantic parsing Gábor Recski
March 16, 2017 2 recent papers on Deep Learning
March 2, 2017 Visualizing and Understanding Recurrent Networks Gábor Borbély