atlas

Research map / Label-efficient and robust learning / Recognition and long-tail

Predict and Constrain: Modeling Cardinality in Deep Structured Prediction

ICML 2018 · Label-efficient and robust learning › Recognition and long-tail · approach: Loss design and classifier theory · 8 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
use Predict and Constrain with input-dependent cardinality prediction and projectiondeep structured prediction model · Bibtexmacro F1: 44.7 -> 45.5Helped
use Predict and Constrain with input-dependent cardinality prediction and projectiondeep structured prediction model · Bookmarksmacro F1: 37.1 -> 39.1Helped
use Predict and Constrain with input-dependent cardinality prediction and projectiondeep structured prediction model · Deliciousmacro F1: 37.8 -> 38.4Helped
replace sigmoid-based cardinality indicators with Predict and Constrain projection (ablation)deep structured prediction model · Bibtexmacro F1: 42.0 -> 45.5Helped
replace differentiable fast exact projection with Predict and Constrain projection (ablation)deep structured prediction model · Bibtexmacro F1: 42.1 -> 45.5Helped
replace sigmoid-based cardinality indicators with Predict and Constrain projection (ablation)deep structured prediction model · Bookmarksmacro F1: 34.6 -> 39.1Helped
replace differentiable fast exact projection with Predict and Constrain projection (ablation)deep structured prediction model · Bookmarksmacro F1: 36.0 -> 39.1Helped
replace sigmoid-based cardinality indicators with Predict and Constrain projection (ablation)deep structured prediction model · Deliciousmacro F1: 34.6 -> 38.4Helped
replace differentiable fast exact projection with Predict and Constrain projection (ablation)deep structured prediction model · Deliciousmacro F1: 34.2 -> 38.4Helped
predict cardinality from input rather than use random or constant cardinalitycardinality predictor on Delicious · DeliciousMSE: 74.9 -> 19.5; 26.9 -> 19.5Helped
use predicted rather than fixed cardinalityPredict and Constrain on Bibtex · Bibtexmacro F1Helped
use predicted rather than fixed cardinalityPredict and Constrain on Bookmarks · Bookmarksmacro F1Hurt

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy