Piero Molino

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Uber ∙ Stanford University

Declarative Machine Learning Systems

In the last years machine learning (ML) has moved from a academic endeav...
07/16/2021 ∙ by Piero Molino, et al. ∙ 13 ∙ share

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Controllable Text Generation with Focused Variation

This work introduces Focused-Variation Network (FVN), a novel model to c...
09/25/2020 ∙ by Lei Shu, et al. ∙ 0 ∙ share

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Joint Contextual Modeling for ASR Correction and Language Understanding

The quality of automatic speech recognition (ASR) is critical to Dialogu...
01/28/2020 ∙ by Yue Weng, et al. ∙ 0 ∙ share

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Exploration Based Language Learning for Text-Based Games

This work presents an exploration and imitation-learning-based agent cap...
01/24/2020 ∙ by Andrea Madotto, et al. ∙ 27 ∙ share

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Plato Dialogue System: A Flexible Conversational AI Research Platform

As the field of Spoken Dialogue Systems and Conversational AI grows, so ...
01/17/2020 ∙ by Alexandros Papangelis, et al. ∙ 18 ∙ share

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Meta-Graph: Few shot Link Prediction via Meta Learning

Fast adaptation to new data is one key facet of human intelligence and i...
12/20/2019 ∙ by Avishek Joey Bose, et al. ∙ 0 ∙ share

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Plug and Play Language Models: a Simple Approach to Controlled Text Generation

Large transformer-based language models (LMs) trained on huge text corpo...
12/04/2019 ∙ by Sumanth Dathathri, et al. ∙ 13 ∙ share

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Ludwig: a type-based declarative deep learning toolbox

In this work we present Ludwig, a flexible, extensible and easy to use t...
09/17/2019 ∙ by Piero Molino, et al. ∙ 16 ∙ share

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Modeling Multi-Action Policy for Task-Oriented Dialogues

Dialogue management (DM) plays a key role in the quality of the interact...
08/30/2019 ∙ by Lei Shu, et al. ∙ 0 ∙ share

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Flexibly-Structured Model for Task-Oriented Dialogues

This paper proposes a novel end-to-end architecture for task-oriented di...
08/06/2019 ∙ by Lei Shu, et al. ∙ 1 ∙ share

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Collaborative Multi-Agent Dialogue Model Training Via Reinforcement Learning

We present the first complete attempt at concurrently training conversat...
07/11/2019 ∙ by Alexandros Papangelis, et al. ∙ 0 ∙ share

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Parallax: Visualizing and Understanding the Semantics of Embedding Spaces via Algebraic Formulae

Embeddings are a fundamental component of many modern machine learning a...
05/28/2019 ∙ by Piero Molino, et al. ∙ 0 ∙ share

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Manifold: A Model-Agnostic Framework for Interpretation and Diagnosis of Machine Learning Models

Interpretation and diagnosis of machine learning models have gained rene...
08/01/2018 ∙ by Jiawei Zhang, et al. ∙ 0 ∙ share

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An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution

Few ideas have enjoyed as large an impact on deep learning as convolutio...
07/09/2018 ∙ by Rosanne Liu, et al. ∙ 6 ∙ share

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COTA: Improving the Speed and Accuracy of Customer Support through Ranking and Deep Networks

For a company looking to provide delightful user experiences, it is of p...
07/03/2018 ∙ by Piero Molino, et al. ∙ 0 ∙ share

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Piero Molino

Featured Co-authors

Yang Wang

Jiawei Zhang

Christopher Ré

Bing Liu

Andrea Madotto

William L. Hamilton

Hu Xu

Jason Yosinski

Gokhan Tur

Lei Shu

Dian Yu

Declarative Machine Learning Systems

Controllable Text Generation with Focused Variation

Joint Contextual Modeling for ASR Correction and Language Understanding

Exploration Based Language Learning for Text-Based Games

Plato Dialogue System: A Flexible Conversational AI Research Platform

Meta-Graph: Few shot Link Prediction via Meta Learning

Plug and Play Language Models: a Simple Approach to Controlled Text Generation

Ludwig: a type-based declarative deep learning toolbox

Modeling Multi-Action Policy for Task-Oriented Dialogues

Flexibly-Structured Model for Task-Oriented Dialogues

Collaborative Multi-Agent Dialogue Model Training Via Reinforcement Learning

Parallax: Visualizing and Understanding the Semantics of Embedding Spaces via Algebraic Formulae

Manifold: A Model-Agnostic Framework for Interpretation and Diagnosis of Machine Learning Models

An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution

COTA: Improving the Speed and Accuracy of Customer Support through Ranking and Deep Networks