ICLR
Collection
Accepted papers for ICLR (International Conference on Learning Representations), one dataset per year. • 14 items • Updated
title stringlengths 14 93 | paper_url stringlengths 45 45 | authors listlengths 1 6 | type stringclasses 2
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values | abstract large_stringlengths 546 1.87k | keywords listlengths 0 0 | TL;DR large_stringclasses 0
values | submission_number int64 2 65 | arxiv_id stringlengths 9 9 ⌀ | arxiv_id_source stringclasses 2
values | embedding listlengths 768 768 |
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The Diagonalized Newton Algorithm for Nonnegative Matrix Factorization | https://openreview.net/forum?id=i87JIQTAnB8AQ | [
"Hugo Van hamme"
] | Poster | null | Non-negative matrix factorization (NMF) has become a popular machine learning approach to many problems in text mining, speech and image processing, bio-informatics and seismic data analysis to name a few. In NMF, a matrix of non-negative data is approximated by the low-rank product of two matrices with non-negative en... | [] | null | 60 | 1301.3389 | title_snapshot | [
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Complexity of Representation and Inference in Compositional Models with
Part Sharing | https://openreview.net/forum?id=ZhGJ9KQlXi9jk | [
"Alan Yuille",
"Roozbeh Mottaghi"
] | Oral | null | This paper describes serial and parallel compositional models of multiple objects with part sharing. Objects are built by part-subpart compositions and expressed in terms of a hierarchical dictionary of object parts. These parts are represented on lattices of decreasing sizes which yield an executive summary descriptio... | [] | null | 34 | 1301.3560 | title_snapshot | [
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Indoor Semantic Segmentation using depth information | https://openreview.net/forum?id=ttnAE7vaATtaK | [
"Camille Couprie",
"Clement Farabet",
"Laurent Najman",
"Yann LeCun"
] | Oral | null | This work addresses multi-class segmentation of indoor scenes with RGB-D inputs. While this area of research has gained much attention recently, most works still rely on hand-crafted features. In contrast, we apply a multiscale convolutional network to learn features directly from the images and the depth information. ... | [] | null | 40 | 1301.3572 | title_snapshot | [
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Metric-Free Natural Gradient for Joint-Training of Boltzmann Machines | https://openreview.net/forum?id=OpvgONa-3WODz | [
"Guillaume Desjardins",
"Razvan Pascanu",
"Aaron Courville",
"Yoshua Bengio"
] | Poster | null | This paper introduces the Metric-Free Natural Gradient (MFNG) algorithm for training Boltzmann Machines. Similar in spirit to the Hessian-Free method of Martens [8], our algorithm belongs to the family of truncated Newton methods and exploits an efficient matrix-vector product to avoid explicitely storing the natural g... | [] | null | 65 | 1301.3545 | title_snapshot | [
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Local Component Analysis | https://openreview.net/forum?id=mLr3In-nbamNu | [
"Nicolas Le Roux",
"Francis Bach"
] | Poster | null | Kernel density estimation, a.k.a. Parzen windows, is a popular density estimation method, which can be used for outlier detection or clustering. With multivariate data, its performance is heavily reliant on the metric used within the kernel. Most earlier work has focused on learning only the bandwidth of the kernel (i.... | [] | null | 64 | 1109.0093 | title_snapshot | [
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Discriminative Recurrent Sparse Auto-Encoders | https://openreview.net/forum?id=aJh-lFL2dFJ21 | [
"Jason Rolfe",
"Yann LeCun"
] | Oral | null | We present the discriminative recurrent sparse auto-encoder model, which consists of an encoder whose hidden layer is recurrent, and two linear decoders, one to reconstruct the input, and one to predict the output. The hidden layer is composed of rectified linear units (ReLU) and is subject to a sparsity penalty. The n... | [] | null | 51 | 1301.3775 | title_snapshot | [
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Training Neural Networks with Stochastic Hessian-Free Optimization | https://openreview.net/forum?id=tFbuFKWX3MFC8 | [
"Ryan Kiros"
] | Poster | null | Hessian-free (HF) optimization has been successfully used for training deep autoencoders and recurrent networks. HF uses the conjugate gradient algorithm to construct update directions through curvature-vector products that can be computed on the same order of time as gradients. In this paper we exploit this property a... | [] | null | 48 | 1301.3641 | title_snapshot | [
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Jitter-Adaptive Dictionary Learning - Application to Multi-Trial Neuroelectric Signals | https://openreview.net/forum?id=4eEO5rd6xSevQ | [
"Sebastian Hitziger",
"Maureen Clerc",
"Alexandre Gramfort",
"Sandrine Saillet",
"Christian Bénar",
"Théodore Papadopoulo"
] | Poster | null | Dictionary Learning has proven to be a powerful tool for many image processing tasks, where atoms are typically defined on small image patches. As a drawback, the dictionary only encodes basic structures. In addition, this approach treats patches of different locations in one single set, which means a loss of informati... | [] | null | 33 | 1301.3611 | title_snapshot | [
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The Neural Representation Benchmark and its Evaluation on Brain and
Machine | https://openreview.net/forum?id=7hXs7GzQHo-QK | [
"Charles Cadieu",
"Ha Hong",
"Dan Yamins",
"Nicolas Pinto",
"Najib J. Majaj",
"James J. DiCarlo"
] | Oral | null | A key requirement for the development of effective learning representations is their evaluation and comparison to representations we know to be effective. In natural sensory domains, the community has viewed the brain as a source of inspiration and as an implicit benchmark for success. However, it has not been possible... | [] | null | 32 | 1301.3530 | title_snapshot | [
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Feature grouping from spatially constrained multiplicative interaction | https://openreview.net/forum?id=4UGuUZWZmi4Ze | [
"Felix Bauer",
"Roland Memisevic"
] | Oral | null | We present a feature learning model that learns to encode relationships between images. The model is defined as a Gated Boltzmann Machine, which is constrained such that hidden units that are nearby in space can gate each other's connections. We show how frequency/orientation 'columns' as well as topographic filter map... | [] | null | 4 | 1301.3391 | title_snapshot | [
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Barnes-Hut-SNE | https://openreview.net/forum?id=eQWJec0ursynH | [
"Laurens van der Maaten"
] | Oral | null | The paper presents an O(N log N)-implementation of t-SNE -- an embedding technique that is commonly used for the visualization of high-dimensional data in scatter plots and that normally runs in O(N^2). The new implementation uses vantage-point trees to compute sparse pairwise similarities between the input data object... | [] | null | 19 | 1301.3342 | title_snapshot | [
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