Early Classification

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

15 shown of 15 papers with code (38 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• ml_edm package: a Python toolkit for Machine Learning based Early Decision Making
  23 Aug 2024 2 repositories listed
  \texttt{ml\_edm} is a Python 3 library, designed for early decision making of any learning tasks involving temporal/sequential data.
• Early Classification of Time Series: Taxonomy and Benchmark
  26 Jun 2024 2 repositories listed
  In many situations, the measurements of a studied phenomenon are provided sequentially, and the prediction of its class needs to be made as early as possible so as not to incur too high a time penalty, but not too early…
• End-to-End Learned Early Classification of Time Series for In-Season Crop Type Mapping
  30 Jan 2019 2 repositories listed
  In this work, we present an End-to-End Learned Early Classification of Time Series (ELECTS) model that estimates a classification score and a probability of whether sufficient data has been observed to come to an early…
• Learning the Optimal Stopping for Early Classification within Finite Horizons via Sequential Probability Ratio Test
  29 Jan 2025 1 repository listed Syntology ran 5 of 8 samples · 3 unverified
  We thus introduce FIRMBOUND, an SPRT-based framework that efficiently estimates the solution to backward induction from training data, bridging the gap between optimal stopping theory and real-world deployment.
• Representation Learning of Tangled Key-Value Sequence Data for Early Classification
  11 Apr 2024 1 repository listed
  To address this problem, we propose a novel method, i.
• AutoML4ETC: Automated Neural Architecture Search for Real-World Encrypted Traffic Classification
  4 Aug 2023 1 repository listed
  However, in production use, it has been shown that a DL classifier's performance inevitably decays over time.
• Multivariate Time Series Early Classification Across Channel and Time Dimensions
  26 Jun 2023 1 repository listed
  Nowadays, the deployment of deep learning models on edge devices for addressing real-world classification problems is becoming more prevalent.
• Dynamic Perceiver for Efficient Visual Recognition
  20 Jun 2023 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  Early exits are placed exclusively within the classification branch, thus eliminating the need for linear separability in low-level features.
• Toward Asymptotic Optimality: Sequential Unsupervised Regression of Density Ratio for Early Classification
  20 Feb 2023 1 repository listed
  Theoretically-inspired sequential density ratio estimation (SDRE) algorithms are proposed for the early classification of time series.
• Stop&Hop: Early Classification of Irregular Time Series
  21 Aug 2022 1 repository listed
  We bridge this gap and study early classification of irregular time series, a new setting for early classifiers that opens doors to more real-world problems.
• Deep Learning-Based Sparse Whole-Slide Image Analysis for the Diagnosis of Gastric Intestinal Metaplasia
  5 Jan 2022 1 repository listed
  We develop an evaluation framework inspired by the early classification literature, in order to quantify the tradeoff between diagnostic performance and inference time for sparse analytic approaches.
• The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization
  28 May 2021 1 repository listed Syntology ran 0 of 6 samples · 6 unverified
  We propose a model for multiclass classification of time series to make a prediction as early and as accurate as possible.
• Interpretable Sequence Classification via Discrete Optimization
  6 Oct 2020 1 repository listed Syntology ran 0 of 3 samples · 3 unverified
  Our automata-based classifiers are interpretable---supporting explanation, counterfactual reasoning, and human-in-the-loop modification---and have strong empirical performance.
• Adaptive-Halting Policy Network for Early Classification
  4 Aug 2019 1 repository listed
  Early classification of time series is the prediction of the class label of a time series before it is observed in its entirety.
• Training Probabilistic Spiking Neural Networks with First-to-spike Decoding
  29 Oct 2017 1 repository listed
  Third-generation neural networks, or Spiking Neural Networks (SNNs), aim at harnessing the energy efficiency of spike-domain processing by building on computing elements that operate on, and exchange, spikes.

Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.