NeurIPS
Collection
Accepted papers for NeurIPS (Conference on Neural Information Processing Systems), one dataset per year. • 13 items • Updated
title string | paper_url string | authors list | type string | primary_area string | abstract large_string | keywords list | TL;DR large_string | submission_number int64 | arxiv_id string | arxiv_id_source string | embedding list |
|---|---|---|---|---|---|---|---|---|---|---|---|
Inferring neural population dynamics from multiple partial recordings of the same neural circuit | https://proceedings.neurips.cc/paper_files/paper/2013/hash/01386bd6d8e091c2ab4c7c7de644d37b-Abstract.html | [
"Srini Turaga",
"Lars Buesing",
"Adam M Packer",
"Henry Dalgleish",
"Noah Pettit",
"Michael Hausser",
"Jakob H Macke"
] | null | null | Simultaneous recordings of the activity of large neural populations are extremely valuable as they can be used to infer the dynamics and interactions of neurons in a local circuit, shedding light on the computations performed. It is now possible to measure the activity of hundreds of neurons using 2-photon calcium imag... | [] | null | 1 | null | null | [
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Approximate Gaussian process inference for the drift function in stochastic differential equations | https://proceedings.neurips.cc/paper_files/paper/2013/hash/021bbc7ee20b71134d53e20206bd6feb-Abstract.html | [
"Andreas Ruttor",
"Philipp Batz",
"Manfred Opper"
] | null | null | We introduce a nonparametric approach for estimating drift functions in systems of stochastic differential equations from incomplete observations of the state vector. Using a Gaussian process prior over the drift as a function of the state vector, we develop an approximate EM algorithm to deal with the unobserved, late... | [] | null | 2 | null | null | [
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Third-Order Edge Statistics: Contour Continuation, Curvature, and Cortical Connections | https://proceedings.neurips.cc/paper_files/paper/2013/hash/024d7f84fff11dd7e8d9c510137a2381-Abstract.html | [
"Matthew Lawlor",
"Steven W Zucker"
] | null | null | Association field models have been used to explain human contour grouping performance and to explain the mean frequency of long-range horizontal connections across cortical columns in V1. However, association fields essentially depend on pairwise statistics of edges in natural scenes. We develop a spectral test of the ... | [] | null | 3 | 1306.3285 | title_snapshot | [
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Transportability from Multiple Environments with Limited Experiments | https://proceedings.neurips.cc/paper_files/paper/2013/hash/02522a2b2726fb0a03bb19f2d8d9524d-Abstract.html | [
"Elias Bareinboim",
"Sanghack Lee",
"Vasant Honavar",
"Judea Pearl"
] | null | null | This paper considers the problem of transferring experimental findings learned from multiple heterogeneous domains to a target environment, in which only limited experiments can be performed. We reduce questions of transportability from multiple domains and with limited scope to symbolic derivations in the do-calculus,... | [] | null | 4 | null | null | [
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On model selection consistency of penalized M-estimators: a geometric theory | https://proceedings.neurips.cc/paper_files/paper/2013/hash/0266e33d3f546cb5436a10798e657d97-Abstract.html | [
"Jason Lee",
"Yuekai Sun",
"Jonathan E Taylor"
] | null | null | Penalized M-estimators are used in diverse areas of science and engineering to fit high-dimensional models with some low-dimensional structure. Often, the penalties are \emph{geometrically decomposable}, \ie\ can be expressed as a sum of (convex) support functions. We generalize the notion of irrepresentable to geometr... | [] | null | 5 | null | null | [
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Robust Bloom Filters for Large MultiLabel Classification Tasks | https://proceedings.neurips.cc/paper_files/paper/2013/hash/043c3d7e489c69b48737cc0c92d0f3a2-Abstract.html | [
"Moustapha M Cisse",
"Nicolas Usunier",
"Thierry Artières",
"Patrick Gallinari"
] | null | null | This paper presents an approach to multilabel classification (MLC) with a large number of labels. Our approach is a reduction to binary classification in which label sets are represented by low dimensional binary vectors. This representation follows the principle of Bloom filters, a space-efficient data structure origi... | [] | null | 6 | null | null | [
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On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation | https://proceedings.neurips.cc/paper_files/paper/2013/hash/05311655a15b75fab86956663e1819cd-Abstract.html | [
"Harikrishna Narasimhan",
"Shivani Agarwal"
] | null | null | We investigate the relationship between three fundamental problems in machine learning: binary classification, bipartite ranking, and binary class probability estimation (CPE). It is known that a good binary CPE model can be used to obtain a good binary classification model (by thresholding at 0.5), and also to obtain ... | [] | null | 7 | null | null | [
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Sequential Transfer in Multi-armed Bandit with Finite Set of Models | https://proceedings.neurips.cc/paper_files/paper/2013/hash/062ddb6c727310e76b6200b7c71f63b5-Abstract.html | [
"Mohammad Gheshlaghi azar",
"Alessandro Lazaric",
"Emma Brunskill"
] | null | null | Learning from prior tasks and transferring that experience to improve future performance is critical for building lifelong learning agents. Although results in supervised and reinforcement learning show that transfer may significantly improve the learning performance, most of the literature on transfer is focused on ba... | [] | null | 8 | 1307.6887 | title_snapshot | [
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A Graphical Transformation for Belief Propagation: Maximum Weight Matchings and Odd-Sized Cycles | https://proceedings.neurips.cc/paper_files/paper/2013/hash/0768281a05da9f27df178b5c39a51263-Abstract.html | [
"Jinwoo Shin",
"Andrew E Gelfand",
"Misha Chertkov"
] | null | null | Max-product ‘belief propagation’ (BP) is a popular distributed heuristic for finding the Maximum A Posteriori (MAP) assignment in a joint probability distribution represented by a Graphical Model (GM). It was recently shown that BP converges to the correct MAP assignment for a class of loopy GMs with the following comm... | [] | null | 9 | 1306.1167 | title_snapshot | [
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A Kernel Test for Three-Variable Interactions | https://proceedings.neurips.cc/paper_files/paper/2013/hash/076a0c97d09cf1a0ec3e19c7f2529f2b-Abstract.html | [
"Dino Sejdinovic",
"Arthur Gretton",
"Wicher Bergsma"
] | null | null | We introduce kernel nonparametric tests for Lancaster three-variable interaction and for total independence, using embeddings of signed measures into a reproducing kernel Hilbert space. The resulting test statistics are straightforward to compute, and are used in powerful three-variable interaction tests, which are con... | [] | null | 10 | 1306.2281 | title_snapshot | [
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Accelerated Mini-Batch Stochastic Dual Coordinate Ascent | https://proceedings.neurips.cc/paper_files/paper/2013/hash/077e29b11be80ab57e1a2ecabb7da330-Abstract.html | [
"Shai Shalev-Shwartz",
"Tong Zhang"
] | null | null | Stochastic dual coordinate ascent (SDCA) is an effective technique for solving regularized loss minimization problems in machine learning. This paper considers an extension of SDCA under the mini-batch setting that is often used in practice. Our main contribution is to introduce an accelerated mini-batch version of SDC... | [] | null | 11 | 1305.2581 | title_snapshot | [
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