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09/21/2023
Boolformer: Symbolic Regression of Logic Functions with Transformers
In this work, we introduce Boolformer, the first Transformer architectur...
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06/12/2023
Transformers learn through gradual rank increase
We identify incremental learning dynamics in transformers, where the dif...
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01/30/2023
Generalization on the Unseen, Logic Reasoning and Degree Curriculum
This paper considers the learning of logical (Boolean) functions with fo...
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11/11/2022
Continuous Soft Pseudo-Labeling in ASR
Continuous pseudo-labeling (PL) algorithms such as slimIPL have recently...
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10/17/2022
Continuous Pseudo-Labeling from the Start
Self-training (ST), or pseudo-labeling has sparked significant interest ...
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05/26/2022
Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures
This paper considers the Pointer Value Retrieval (PVR) benchmark introdu...
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07/27/2021
Pointer Value Retrieval: A new benchmark for understanding the limits of neural network generalization
The successes of deep learning critically rely on the ability of neural ...
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02/19/2021
Training cascaded networks for speeded decisions using a temporal-difference loss
Although deep feedforward neural networks share some characteristics wit...
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12/14/2020
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning
Understanding generalization in deep learning is arguably one of the mos...
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11/05/2020
Data Augmentation via Structured Adversarial Perturbations
Data augmentation is a major component of many machine learning methods ...
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10/06/2020
Characterising Bias in Compressed Models
The popularity and widespread use of pruning and quantization is driven ...
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01/14/2020
Auto Completion of User Interface Layout Design Using Transformer-Based Tree Decoders
It has been of increasing interest in the field to develop automatic mac...
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12/04/2019
Fantastic Generalization Measures and Where to Find Them
Generalization of deep networks has been of great interest in recent yea...
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09/19/2019
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
An important research direction in machine learning has centered around ...
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07/24/2019
Efficient Exploration with Self-Imitation Learning via Trajectory-Conditioned Policy
This paper proposes a method for learning a trajectory-conditioned polic...
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06/11/2019
Parallel Scheduled Sampling
Auto-regressive models are widely used in sequence generation problems. ...
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06/10/2019
A Closed-Form Learned Pooling for Deep Classification Networks
In modern computer vision tasks, convolutional neural networks (CNNs) ar...
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05/20/2019
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
Graph convolutional network (GCN) has been successfully applied to many ...
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03/04/2019
Do Neural Networks Show Gestalt Phenomena? An Exploration of the Law of Closure
One characteristic of human visual perception is the presence of "Gestal...
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02/14/2019
Transfusion: Understanding Transfer Learning with Applications to Medical Imaging
With the increasingly varied applications of deep learning, transfer lea...
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02/13/2019
Identity Crisis: Memorization and Generalization under Extreme Overparameterization
We study the interplay between memorization and generalization of overpa...
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02/06/2019
Are All Layers Created Equal?
Understanding learning and generalization of deep architectures has been...
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01/29/2019
Semantic Redundancies in Image-Classification Datasets: The 10 Don't Need
Large datasets have been crucial to the success of deep learning models ...
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01/25/2019
Unsupervised speech representation learning using WaveNet autoencoders
We consider the task of unsupervised extraction of meaningful latent rep...
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11/27/2018
GaterNet: Dynamic Filter Selection in Convolutional Neural Network via a Dedicated Global Gating Network
The concept of conditional computation for deep nets has been proposed p...
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11/03/2018
Content preserving text generation with attribute controls
In this work, we address the problem of modifying textual attributes of ...
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10/23/2018
Area Attention
Existing attention mechanisms, are mostly item-based in that a model is ...
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09/28/2018
Predicting the Generalization Gap in Deep Networks with Margin Distributions
As shown in recent research, deep neural networks can perfectly fit rand...
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06/14/2018
Insights on representational similarity in neural networks with canonical correlation
Comparing different neural network representations and determining how r...
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04/18/2018
A Study on Overfitting in Deep Reinforcement Learning
Recent years have witnessed significant progresses in deep Reinforcement...
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03/31/2018
Adversarial Attacks and Defences Competition
To accelerate research on adversarial examples and robustness of machine...
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03/16/2018
Tensor2Tensor for Neural Machine Translation
Tensor2Tensor is a library for deep learning models that is well-suited ...
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03/15/2018
Large Margin Deep Networks for Classification
We present a formulation of deep learning that aims at producing a large...
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03/13/2018
Predicting Human Performance in Vertical Menu Selection Using Deep Learning
Predicting human performance in interaction tasks allows designers or de...
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03/09/2018
Fast Decoding in Sequence Models using Discrete Latent Variables
Autoregressive sequence models based on deep neural networks, such as RN...
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01/29/2018
Discrete Autoencoders for Sequence Models
Recurrent models for sequences have been recently successful at many tas...
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12/22/2017
On Using Backpropagation for Speech Texture Generation and Voice Conversion
Inspired by recent work on neural network image generation which rely on...
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06/13/2017
Device Placement Optimization with Reinforcement Learning
The past few years have witnessed a growth in size and computational req...
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03/31/2017
N-gram Language Modeling using Recurrent Neural Network Estimation
We investigate the effective memory depth of RNN models by using them fo...
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03/29/2017
Tacotron: Towards End-to-End Speech Synthesis
A text-to-speech synthesis system typically consists of multiple stages,...
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03/15/2017
Sharp Minima Can Generalize For Deep Nets
Despite their overwhelming capacity to overfit, deep learning architectu...
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01/11/2017
Context-aware Captions from Context-agnostic Supervision
We introduce an inference technique to produce discriminative context-aw...
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11/29/2016
Neural Combinatorial Optimization with Reinforcement Learning
This paper presents a framework to tackle combinatorial optimization pro...
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11/04/2016
Adversarial Machine Learning at Scale
Adversarial examples are malicious inputs designed to fool machine learn...
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10/27/2016
Can Active Memory Replace Attention?
Several mechanisms to focus attention of a neural network on selected pa...
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09/21/2016
Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge
Automatically describing the content of an image is a fundamental proble...
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07/08/2016
Adversarial examples in the physical world
Most existing machine learning classifiers are highly vulnerable to adve...
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05/27/2016
Density estimation using Real NVP
Unsupervised learning of probabilistic models is a central yet challengi...
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04/04/2016
Revisiting Distributed Synchronous SGD
Distributed training of deep learning models on large-scale training dat...
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11/19/2015
