Search Results for author: Julian McAuley

Found 78 papers, 39 papers with code

Interview: Large-scale Modeling of Media Dialog with Discourse Patterns and Knowledge Grounding

no code implementations EMNLP 2020 Bodhisattwa Prasad Majumder, Shuyang Li, Jianmo Ni, Julian McAuley

In this work, we perform the first large-scale analysis of discourse in media dialog and its impact on generative modeling of dialog turns, with a focus on interrogative patterns and use of external knowledge.

Rethink, Revisit, Revise: A Spiral Reinforced Self-Revised Network for Zero-Shot Learning

no code implementations1 Dec 2021 Zhe Liu, Yun Li, Lina Yao, Julian McAuley, Sam Dixon

Our framework outperforms state-of-the-art algorithms on four benchmark datasets in both zero-shot and generalized zero-shot settings, which demonstrates the effectiveness of spiral learning in learning generalizable and complex correlations.

Zero-Shot Learning

An Entropy-guided Reinforced Partial Convolutional Network for Zero-Shot Learning

no code implementations3 Nov 2021 Yun Li, Zhe Liu, Lina Yao, Xianzhi Wang, Julian McAuley, Xiaojun Chang

Zero-Shot Learning (ZSL) aims to transfer learned knowledge from observed classes to unseen classes via semantic correlations.

Generalized Zero-Shot Learning

Locality-Sensitive Experience Replay for Online Recommendation

no code implementations21 Oct 2021 Xiaocong Chen, Lina Yao, Xianzhi Wang, Julian McAuley

Existing studies encourage the agent to learn from past experience via experience replay (ER).

Recommendation Systems

Weakly Supervised Contrastive Learning for Chest X-Ray Report Generation

no code implementations Findings (EMNLP) 2021 An Yan, Zexue He, Xing Lu, Jiang Du, Eric Chang, Amilcare Gentili, Julian McAuley, Chun-Nan Hsu

Radiology report generation aims at generating descriptive text from radiology images automatically, which may present an opportunity to improve radiology reporting and interpretation.

Contrastive Learning Medical Report Generation +1

Modeling Dynamic Attributes for Next Basket Recommendation

no code implementations23 Sep 2021 Yongjun Chen, Jia Li, Chenghao Liu, Chenxi Li, Markus Anderle, Julian McAuley, Caiming Xiong

However, properly integrating them into user interest models is challenging since attribute dynamics can be diverse such as time-interval aware, periodic patterns (etc.

Next-basket recommendation

A Survey of Deep Reinforcement Learning in Recommender Systems: A Systematic Review and Future Directions

no code implementations8 Sep 2021 Xiaocong Chen, Lina Yao, Julian McAuley, Guanglin Zhou, Xianzhi Wang

In light of the emergence of deep reinforcement learning (DRL) in recommender systems research and several fruitful results in recent years, this survey aims to provide a timely and comprehensive overview of the recent trends of deep reinforcement learning in recommender systems.

Recommendation Systems

Beyond Preserved Accuracy: Evaluating Loyalty and Robustness of BERT Compression

1 code implementation EMNLP 2021 Canwen Xu, Wangchunshu Zhou, Tao Ge, Ke Xu, Julian McAuley, Furu Wei

Recent studies on compression of pretrained language models (e. g., BERT) usually use preserved accuracy as the metric for evaluation.

Knowledge Distillation Quantization

Black-Box Attacks on Sequential Recommenders via Data-Free Model Extraction

1 code implementation1 Sep 2021 Zhenrui Yue, Zhankui He, Huimin Zeng, Julian McAuley

Under this setting, we propose an API-based model extraction method via limited-budget synthetic data generation and knowledge distillation.

Data Poisoning Knowledge Distillation +4

Contrastive Self-supervised Sequential Recommendation with Robust Augmentation

1 code implementation14 Aug 2021 Zhiwei Liu, Yongjun Chen, Jia Li, Philip S. Yu, Julian McAuley, Caiming Xiong

In this paper, we investigate the application of contrastive Self-Supervised Learning (SSL) to the sequential recommendation, as a way to alleviate some of these issues.

Contrastive Learning Self-Supervised Learning

An Empirical Evaluation of End-to-End Polyphonic Optical Music Recognition

1 code implementation3 Aug 2021 Sachinda Edirisooriya, Hao-Wen Dong, Julian McAuley, Taylor Berg-Kirkpatrick

Monophonic and homophonic music can be described as homorhythmic, or having a single musical rhythm.

Towards Automatic Instrumentation by Learning to Separate Parts in Symbolic Multitrack Music

1 code implementation13 Jul 2021 Hao-Wen Dong, Chris Donahue, Taylor Berg-Kirkpatrick, Julian McAuley

In this paper, we aim to further extend this idea and examine the feasibility of automatic instrumentation -- dynamically assigning instruments to notes in solo music during performance.

Multi-class Classification

SVP-CF: Selection via Proxy for Collaborative Filtering Data

no code implementations11 Jul 2021 Noveen Sachdeva, Carole-Jean Wu, Julian McAuley

As we demonstrate, commonly-used data sampling schemes can have significant consequences on algorithm performance -- masking performance deficiencies in algorithms or altering the relative performance of algorithms, as compared to models trained on the complete dataset.

Collaborative Filtering Recommendation Systems

Rationale-Inspired Natural Language Explanations with Commonsense

no code implementations25 Jun 2021 Bodhisattwa Prasad Majumder, Oana-Maria Camburu, Thomas Lukasiewicz, Julian McAuley

More precisely, we introduce a unified framework, called RExC (Rationale-Inspired Explanations with Commonsense), that (1) extracts rationales as a set of features responsible for machine predictions, (2) expands the extractive rationales using available commonsense resources, and (3) uses the expanded knowledge to generate natural language explanations.

Language understanding

Unsupervised Enrichment of Persona-grounded Dialog with Background Stories

1 code implementation ACL 2021 Bodhisattwa Prasad Majumder, Taylor Berg-Kirkpatrick, Julian McAuley, Harsh Jhamtani

Humans often refer to personal narratives, life experiences, and events to make a conversation more engaging and rich.

Meta Learning for Knowledge Distillation

1 code implementation8 Jun 2021 Wangchunshu Zhou, Canwen Xu, Julian McAuley

We present Meta Learning for Knowledge Distillation (MetaDistil), a simple yet effective alternative to traditional knowledge distillation (KD) methods where the teacher model is fixed during training.

Knowledge Distillation Meta-Learning

SHARE: a System for Hierarchical Assistive Recipe Editing

no code implementations17 May 2021 Shuyang Li, Yufei Li, Jianmo Ni, Julian McAuley

We introduce SHARE: a System for Hierarchical Assistive Recipe Editing to assist home cooks with dietary restrictions -- a population under-served by existing cooking resources.

Recipe Generation

Ask what's missing and what's useful: Improving Clarification Question Generation using Global Knowledge

1 code implementation NAACL 2021 Bodhisattwa Prasad Majumder, Sudha Rao, Michel Galley, Julian McAuley

The ability to generate clarification questions i. e., questions that identify useful missing information in a given context, is important in reducing ambiguity.

Question Generation

Cross-modal Adversarial Reprogramming

1 code implementation15 Feb 2021 Paarth Neekhara, Shehzeen Hussain, Jinglong Du, Shlomo Dubnov, Farinaz Koushanfar, Julian McAuley

Recent works on adversarial reprogramming have shown that it is possible to repurpose neural networks for alternate tasks without modifying the network architecture or parameters.

Classification General Classification +1

Expressive Neural Voice Cloning

no code implementations30 Jan 2021 Paarth Neekhara, Shehzeen Hussain, Shlomo Dubnov, Farinaz Koushanfar, Julian McAuley

In this work, we propose a controllable voice cloning method that allows fine-grained control over various style aspects of the synthesized speech for an unseen speaker.

Speech Synthesis Style Transfer

Like hiking? You probably enjoy nature: Persona-grounded Dialog with Commonsense Expansions

1 code implementation EMNLP 2020 Bodhisattwa Prasad Majumder, Harsh Jhamtani, Taylor Berg-Kirkpatrick, Julian McAuley

Existing persona-grounded dialog models often fail to capture simple implications of given persona descriptions, something which humans are able to do seamlessly.

Learning Visual-Semantic Embeddings for Reporting Abnormal Findings on Chest X-rays

no code implementations Findings of the Association for Computational Linguistics 2020 Jianmo Ni, Chun-Nan Hsu, Amilcare Gentili, Julian McAuley

In this work, we focus on reporting abnormal findings on radiology images; instead of training on complete radiology reports, we propose a method to identify abnormal findings from the reports in addition to grouping them with unsupervised clustering and minimal rules.

Cross-Modal Retrieval Text Generation

MusPy: A Toolkit for Symbolic Music Generation

2 code implementations5 Aug 2020 Hao-Wen Dong, Ke Chen, Julian McAuley, Taylor Berg-Kirkpatrick

MusPy provides easy-to-use tools for essential components in a music generation system, including dataset management, data I/O, data preprocessing and model evaluation.

Music Generation

BERT Loses Patience: Fast and Robust Inference with Early Exit

1 code implementation NeurIPS 2020 Wangchunshu Zhou, Canwen Xu, Tao Ge, Julian McAuley, Ke Xu, Furu Wei

In this paper, we propose Patience-based Early Exit, a straightforward yet effective inference method that can be used as a plug-and-play technique to simultaneously improve the efficiency and robustness of a pretrained language model (PLM).

Language Modelling

How Useful are Reviews for Recommendation? A Critical Review and Potential Improvements

1 code implementation25 May 2020 Noveen Sachdeva, Julian McAuley

We investigate a growing body of work that seeks to improve recommender systems through the use of review text.

Recommendation Systems

Speech Recognition and Multi-Speaker Diarization of Long Conversations

2 code implementations16 May 2020 Huanru Henry Mao, Shuyang Li, Julian McAuley, Garrison Cottrell

Speech recognition (ASR) and speaker diarization (SD) models have traditionally been trained separately to produce rich conversation transcripts with speaker labels.

Data Augmentation Speaker Diarization +1

Interview: A Large-Scale Open-Source Corpus of Media Dialog

no code implementations7 Apr 2020 Bodhisattwa Prasad Majumder, Shuyang Li, Jianmo Ni, Julian McAuley

Compared to existing large-scale proxies for conversational data, language models trained on our dataset exhibit better zero-shot out-of-domain performance on existing spoken dialog datasets, demonstrating its usefulness in modeling real-world conversations.

Developing a Recommendation Benchmark for MLPerf Training and Inference

no code implementations16 Mar 2020 Carole-Jean Wu, Robin Burke, Ed H. Chi, Joseph Konstan, Julian McAuley, Yves Raimond, Hao Zhang

Deep learning-based recommendation models are used pervasively and broadly, for example, to recommend movies, products, or other information most relevant to users, in order to enhance the user experience.

Image Classification Object Detection +2

ReZero is All You Need: Fast Convergence at Large Depth

13 code implementations10 Mar 2020 Thomas Bachlechner, Bodhisattwa Prasad Majumder, Huanru Henry Mao, Garrison W. Cottrell, Julian McAuley

Deep networks often suffer from vanishing or exploding gradients due to inefficient signal propagation, leading to long training times or convergence difficulties.

Language Modelling

TiSASRec: Time Interval Aware Self-Attention for Sequential Recommendation

2 code implementations1 Jan 2020 Jiacheng Li, Yujie Wang, Julian McAuley

Sequential recommender systems seek to exploit the order of users' interactions, in order to predict their next action based on the context of what they have done recently.

Recommendation Systems

Addressing Marketing Bias in Product Recommendations

1 code implementation4 Dec 2019 Mengting Wan, Jianmo Ni, Rishabh Misra, Julian McAuley

However, these interactions can be biased by how the product is marketed, for example due to the selection of a particular human model in a product image.

Collaborative Filtering Fairness +1

Justifying Recommendations using Distantly-Labeled Reviews and Fine-Grained Aspects

no code implementations IJCNLP 2019 Jianmo Ni, Jiacheng Li, Julian McAuley

Several recent works have considered the problem of generating reviews (or {`}tips{'}) as a form of explanation as to why a recommendation might match a customer{'}s interests.

Decision Making Language Modelling

Candidate Generation with Binary Codes for Large-Scale Top-N Recommendation

no code implementations12 Sep 2019 Wang-Cheng Kang, Julian McAuley

Generating the Top-N recommendations from a large corpus is computationally expensive to perform at scale.

Recommendation Systems Re-Ranking

Scalable and Accurate Dialogue State Tracking via Hierarchical Sequence Generation

1 code implementation IJCNLP 2019 Liliang Ren, Jianmo Ni, Julian McAuley

Experiments on both the multi-domain and the single domain dialogue state tracking dataset show that our model not only scales easily with the increasing number of pre-defined domains and slots but also reaches the state-of-the-art performance.

Dialogue State Tracking Multi-domain Dialogue State Tracking

Generating Personalized Recipes from Historical User Preferences

1 code implementation IJCNLP 2019 Bodhisattwa Prasad Majumder, Shuyang Li, Jianmo Ni, Julian McAuley

Existing approaches to recipe generation are unable to create recipes for users with culinary preferences but incomplete knowledge of ingredients in specific dishes.

Recipe Generation Text Generation

Fine-Grained Spoiler Detection from Large-Scale Review Corpora

no code implementations ACL 2019 Mengting Wan, Rishabh Misra, Ndapa Nakashole, Julian McAuley

This paper presents computational approaches for automatically detecting critical plot twists in reviews of media products.

Universal Adversarial Perturbations for Speech Recognition Systems

no code implementations9 May 2019 Paarth Neekhara, Shehzeen Hussain, Prakhar Pandey, Shlomo Dubnov, Julian McAuley, Farinaz Koushanfar

In this work, we demonstrate the existence of universal adversarial audio perturbations that cause mis-transcription of audio signals by automatic speech recognition (ASR) systems.

automatic-speech-recognition Speech Recognition

Expediting TTS Synthesis with Adversarial Vocoding

1 code implementation16 Apr 2019 Paarth Neekhara, Chris Donahue, Miller Puckette, Shlomo Dubnov, Julian McAuley

Recent approaches in text-to-speech (TTS) synthesis employ neural network strategies to vocode perceptually-informed spectrogram representations directly into listenable waveforms.

Embryo staging with weakly-supervised region selection and dynamically-decoded predictions

no code implementations9 Apr 2019 Tingfung Lau, Nathan Ng, Julian Gingold, Nina Desai, Julian McAuley, Zachary C. Lipton

First, noting that in each image the embryo occupies a small subregion, we jointly train a region proposal network with the downstream classifier to isolate the embryo.

Region Proposal

Complete the Look: Scene-based Complementary Product Recommendation

1 code implementation CVPR 2019 Wang-Cheng Kang, Eric Kim, Jure Leskovec, Charles Rosenberg, Julian McAuley

We design an approach to extract training data for this task, and propose a novel way to learn the scene-product compatibility from fashion or interior design images.

Product Recommendation

Recommendation Through Mixtures of Heterogeneous Item Relationships

2 code implementations29 Aug 2018 Wang-Cheng Kang, Mengting Wan, Julian McAuley

Recommender Systems have proliferated as general-purpose approaches to model a wide variety of consumer interaction data.

Knowledge Graph Embeddings Recommendation Systems

Self-Attentive Sequential Recommendation

4 code implementations20 Aug 2018 Wang-Cheng Kang, Julian McAuley

Sequential dynamics are a key feature of many modern recommender systems, which seek to capture the `context' of users' activities on the basis of actions they have performed recently.

Recommendation Systems

Visually-Aware Personalized Recommendation using Interpretable Image Representations

no code implementations26 Jun 2018 Charles Packer, Julian McAuley, Arnau Ramisa

Visually-aware recommender systems use visual signals present in the underlying data to model the visual characteristics of items and users' preferences towards them.

Recommendation Systems

The NES Music Database: A multi-instrumental dataset with expressive performance attributes

2 code implementations12 Jun 2018 Chris Donahue, Huanru Henry Mao, Julian McAuley

Existing research on music generation focuses on composition, but often ignores the expressive performance characteristics required for plausible renditions of resultant pieces.

Music Generation

Adversarial Audio Synthesis

17 code implementations ICLR 2019 Chris Donahue, Julian McAuley, Miller Puckette

Audio signals are sampled at high temporal resolutions, and learning to synthesize audio requires capturing structure across a range of timescales.

Audio Generation Image Generation

Does mitigating ML's impact disparity require treatment disparity?

no code implementations NeurIPS 2018 Zachary C. Lipton, Alexandra Chouldechova, Julian McAuley

Following related work in law and policy, two notions of disparity have come to shape the study of fairness in algorithmic decision-making.

Decision Making Fairness

Visually-Aware Fashion Recommendation and Design with Generative Image Models

no code implementations7 Nov 2017 Wang-Cheng Kang, Chen Fang, Zhaowen Wang, Julian McAuley

Here, we seek to extend this contribution by showing that recommendation performance can be significantly improved by learning `fashion aware' image representations directly, i. e., by training the image representation (from the pixel level) and the recommender system jointly; this contribution is related to recent work using Siamese CNNs, though we are able to show improvements over state-of-the-art recommendation techniques such as BPR and variants that make use of pre-trained visual features.

Recommendation Systems

Estimating Reactions and Recommending Products with Generative Models of Reviews

no code implementations IJCNLP 2017 Jianmo Ni, Zachary C. Lipton, Sharad Vikram, Julian McAuley

Natural language approaches that model information like product reviews have proved to be incredibly useful in improving the performance of such methods, as reviews provide valuable auxiliary information that can be used to better estimate latent user preferences and item properties.

Collaborative Filtering Language Modelling +2

Translation-based Recommendation

1 code implementation8 Jul 2017 Ruining He, Wang-Cheng Kang, Julian McAuley

Modeling the complex interactions between users and items as well as amongst items themselves is at the core of designing successful recommender systems.

Recommendation Systems Translation

Dance Dance Convolution

1 code implementation ICML 2017 Chris Donahue, Zachary C. Lipton, Julian McAuley

For the step placement task, we combine recurrent and convolutional neural networks to ingest spectrograms of low-level audio features to predict steps, conditioned on chart difficulty.

Predicting Surgery Duration with Neural Heteroscedastic Regression

no code implementations17 Feb 2017 Nathan Ng, Rodney A Gabriel, Julian McAuley, Charles Elkan, Zachary C. Lipton

Scheduling surgeries is a challenging task due to the fundamental uncertainty of the clinical environment, as well as the risks and costs associated with under- and over-booking.

Modeling Ambiguity, Subjectivity, and Diverging Viewpoints in Opinion Question Answering Systems

no code implementations25 Oct 2016 Mengting Wan, Julian McAuley

Product review websites provide an incredible lens into the wide variety of opinions and experiences of different people, and play a critical role in helping users discover products that match their personal needs and preferences.

Question Answering

Fusing Similarity Models with Markov Chains for Sparse Sequential Recommendation

no code implementations28 Sep 2016 Ruining He, Julian McAuley

We show quantitatively that Fossil outperforms alternative algorithms, especially on sparse datasets, and qualitatively that it captures personalized dynamics and is able to make meaningful recommendations.

Recommendation Systems

Vista: A Visually, Socially, and Temporally-aware Model for Artistic Recommendation

no code implementations15 Jul 2016 Ruining He, Chen Fang, Zhaowen Wang, Julian McAuley

Understanding users' interactions with highly subjective content---like artistic images---is challenging due to the complex semantics that guide our preferences.

Recommendation Systems

Sherlock: Sparse Hierarchical Embeddings for Visually-aware One-class Collaborative Filtering

no code implementations20 Apr 2016 Ruining He, Chunbin Lin, Jianguo Wang, Julian McAuley

Building successful recommender systems requires uncovering the underlying dimensions that describe the properties of items as well as users' preferences toward them.

Collaborative Filtering Recommendation Systems

Learning Compatibility Across Categories for Heterogeneous Item Recommendation

no code implementations31 Mar 2016 Ruining He, Charles Packer, Julian McAuley

Identifying relationships between items is a key task of an online recommender system, in order to help users discover items that are functionally complementary or visually compatible.

Product Recommendation Recommendation Systems

Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering

no code implementations4 Feb 2016 Ruining He, Julian McAuley

Building a successful recommender system depends on understanding both the dimensions of people's preferences as well as their dynamics.

Collaborative Filtering Recommendation Systems

Addressing Complex and Subjective Product-Related Queries with Customer Reviews

no code implementations21 Dec 2015 Julian McAuley, Alex Yang

In this paper we hope to fuse these two paradigms: given a large volume of previously answered queries about products, we hope to automatically learn whether a review of a product is relevant to a given query.

Generative Concatenative Nets Jointly Learn to Write and Classify Reviews

1 code implementation11 Nov 2015 Zachary C. Lipton, Sharad Vikram, Julian McAuley

A recommender system's basic task is to estimate how users will respond to unseen items.

VBPR: Visual Bayesian Personalized Ranking from Implicit Feedback

5 code implementations6 Oct 2015 Ruining He, Julian McAuley

In this paper we propose a scalable factorization model to incorporate visual signals into predictors of people's opinions, which we apply to a selection of large, real-world datasets.

Recommendation Systems

Image-based Recommendations on Styles and Substitutes

no code implementations15 Jun 2015 Julian McAuley, Christopher Targett, Qinfeng Shi, Anton Van Den Hengel

Humans inevitably develop a sense of the relationships between objects, some of which are based on their appearance.

From Amateurs to Connoisseurs: Modeling the Evolution of User Expertise through Online Reviews

no code implementations18 Mar 2013 Julian McAuley, Jure Leskovec

Recommending products to consumers means not only understanding their tastes, but also understanding their level of experience.

Image Labeling on a Network: Using Social-Network Metadata for Image Classification

no code implementations16 Jul 2012 Julian McAuley, Jure Leskovec

Many of these benchmarks are derived from online photo sharing networks, like Flickr, which in addition to hosting images also provide a highly interactive social community.

General Classification Image Classification +1

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