Concept

Natural-language user interface

Publications associées (148)

Wearable Technologies for Embodied Human-Robot Interaction

Robotic teleoperation is fundamental to augment the resilience, precision, and force of robots with the cognition of the operator. However, current interfaces, such as joysticks and remote controllers, are often complicated to handle since they require cog ...

EPFL2019

Architectural Sampling: A Formal Basis for Machine-Learnable Architecture

Immanuel Chee Beng Koh

The spatial and formal conception of architecture, and thus its modes of design perception and representation, directly contributes to its machine-learnability; and consequently, its capacity in leveraging today's machine learning apparatus for design inno ...

EPFL2019

A Framework for Adaptive User Interface Generation based on User Behavioural Patterns

The concept of adaptivity is crucial in enterprise software systems with a large user base. Adaptive user interfaces (AUI) is an emerging research area that enables customized user experience based on user activities. Most of the existing studies that are ...

IEEE2019

Better Word Embeddings by Disentangling Contextual n-Gram Information

Martin Jaggi, Matteo Pagliardini, Prakhar Gupta

Pre-trained word vectors are ubiquitous in Natural Language Processing applications. In this paper, we show how training word embeddings jointly with bigram and even trigram embeddings, results in improved unigram embeddings. We claim that training word em ...

2019

Historical Newspaper User Interfaces: A Review

Maud Ehrmann

After decades of large-scale digitization, many historical newspaper collections are just one click away via online portals developed and supported by various public or private stakeholders. Initially offering access to full text search and facsimiles visu ...

IFLA Library2019

Learning Entailment-Based Sentence Embeddings from Natural Language Inference

James Henderson, Rabeeh Karimi Mahabadi, Jan Frederik Jonas Florian Mai

Large datasets on natural language inference are a potentially valuable resource for inducing semantic representations of natural language sentences. But in many such models the embeddings computed by the sentence encoder goes through an MLP-based interact ...

Idiap2019

Overcoming Multi-model Forgetting

Mathieu Salzmann, Anthony Christopher Davison, Martin Jaggi, Yassine Benyahia, Claudiu-Cristian Musat, Kaicheng Yu

We identify a phenomenon, which we refer to as multi-model forgetting, that occurs when sequentially training multiple deep networks with partially-shared parameters; the performance of previously-trained models degrades as one optimizes a subsequent one, ...

JMLR2019

Feed-forwards meet recurrent networks in vehicle trajectory prediction

Alexandre Massoud Alahi, Mohammadhossein Bahari

For an autonomous car, getting surprised is the worst thing that can happen. To prevent that, plenty of studies are trying to forecast traffic participants’ actions especially in an urban scene using recurrent networks. Recurrent networks are used for temp ...

2019

Determining the Optimal Phase-Change Material via High-Throughput Calculations

Amina Matt

The discovery and optimization of phase-change and shape memory alloys remain a tedious and expensive process. Here a simple computational method is proposed to determine the ideal phase- change material for a given alloy composed of three elements. Using ...

2019

Unified and Scalable Incremental Recommenders with Consumed Item Packs

Rachid Guerraoui, Rhicheek Patra

Recommenders personalize the web content using collaborative filtering to relate users (or items). This work proposes to unify user-based, item-based and neural word embeddings types of recommenders under a single abstraction for their input, we name Consu ...

Springer2019

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