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ServiceNow AI Research
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ServiceNow AI Research
1
Equivariant Adaptation of Large Pre-Trained Models
Equivariant networks are specifically designed to ensure consistent behavior with respect to a set of input transformations, leading to …
Arnab Mondal
,
Siba Smarak Panigrahi
,
Sai Rajeswar Mudumba
,
Siamak Ravanbakhsh
Conference on Neural Information Processing Systems (NeurIPS), 2023.
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Group Robust Classification Without Any Group Information
Empirical risk minimization (ERM) is sensitive to spurious correlations present in training data, which poses a significant risk when …
Christos Tsirigotis
,
João Monteiro
,
Pau Rodriguez
,
Aaron Courville
Conference on Neural Information Processing Systems (NeurIPS), 2023.
Paper
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Code
Let's Make Block Coordinate Descent Converge Faster: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence
Block coordinate descent (BCD) methods are widely used for large-scale numerical optimization because of their cheap iteration costs, …
julie nutini
,
Issam H. Laradji
,
Mark Schmidt
International Conference on Machine Learning (ICML), 2023.
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Code
Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels
Controlling artificial agents from visual sensory data is an arduous task. Reinforcement learning (RL) algorithms can succeed but …
Sai Rajeswar Mudumba
,
Pietro Mazzaglia
,
Tim Verbelen
,
Alexandre Piche
,
Bart Dhoedt
,
Aaron Courville
,
Alexandre Lacoste
International Conference on Machine Learning (ICML), 2023.
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Code
Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts
Multivariate probabilistic time series forecasts are commonly evaluated via proper scoring rules, i.e., functions that are minimal in …
Étienne Marcotte
,
Valentina Zantedeschi
,
Alexandre Drouin
,
Nicolas Chapados
International Conference on Machine Learning (ICML), 2023.
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Slides
Video
Affinity Learning With Blind-spot Self-supervision for Image Denoising
In this paper, we extend the blind-spot based self-supervised denoising by using affinity learning to remove noise from affected …
Yuhongze Zhou
,
Liguang Zhou
,
Issam H. Laradji
,
Tin Lun Lam
,
Yangsheng Xu
International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023.
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Breadth-First Pipeline Parallelism
We introduce Breadth-First Pipeline Parallelism, a novel training schedule which optimizes the combination of pipeline and data …
Joel Lamy Poirier
Conference on Machine Learning and Systems (MLSYS), 2023.
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MAPL: Parameter-Efficient Adaptation of Unimodal Pre-Trained Models for Vision-Language Few-Shot Prompting
Large pre-trained models have proved to be remarkable zero- and (prompt-based) few-shot learners in unimodal vision and language tasks. …
Oscar Manas
,
Pau Rodriguez
,
Saba Ahmadi
,
Aida Nematzadeh
,
Yash Goyal
,
Aishwarya Agrawal
European Chapter of the Association for Computational Linguistics (EACL), 2023.
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The StatCan Dialogue Dataset: Retrieving Data Tables through Conversations with Genuine Intents
We introduce the StatCan Dialogue Dataset consisting of 4967 conversations between agents working at Statistics Canada and online users …
Xing Han Lu
,
Siva Reddy
,
Harm de Vries
European Chapter of the Association for Computational Linguistics (EACL), 2023.
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Choreographer: Learning and Adapting Skills in Imagination
Unsupervised skill learning aims to learn a rich repertoire of behaviors without external supervision, providing artificial agents with …
Pietro Mazzaglia
,
Tim Verbelen
,
Bart Dhoedt
,
Alexandre Lacoste
,
Sai Rajeswar Mudumba
International Conference of Learning Representations (ICLR), 2023.
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