Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Learning With Subquadratic Regularization : A Primal-Dual Approach
Authors: Raman Sankaran, Francis Bach, Chiranjib Bhattacharyya
IJCAI 2020 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | 6 Experiments To illustrate the efficiency of CP-η and ADMM-η over existing algorithms, we choose the aforementioned tree-sparsity inducing norm ΩH (Example 1)... Setup. We perform numerical simulations2 by generating synthetic data... We make the following inferences from the simulation plots given in Figure 1. |
| Researcher Affiliation | Collaboration | Raman Sankaran1,3 , Francis Bach2 and Chiranjib Bhattacharyya3 1Linked In, Bengaluru 2INRIA Ecole Normale Sup erieure PSL Research University, Paris 3Indian Institute of Science, Bengaluru |
| Pseudocode | Yes | Algorithm 1 CP [Chambolle and Pock, 2011]... Algorithm 2 ADMM-η... Algorithm 3 CP-η |
| Open Source Code | No | The paper does not provide any specific links to open-source code for the methodology described, nor does it explicitly state that the code is publicly available. |
| Open Datasets | No | We perform numerical simulations by generating synthetic data. Following [Bach et al., 2011], we generate X Rn d as Xij N(0, 1). |
| Dataset Splits | No | The paper performs numerical simulations by generating synthetic data and sets parameters like n, d, and λ, but it does not specify train, validation, or test dataset splits or cross-validation settings. |
| Hardware Specification | Yes | Conducted on a Ubuntu PC with Core i7 processor, 8G RAM. |
| Software Dependencies | No | The paper mentions running experiments on a 'Ubuntu PC' but does not specify any software dependencies (e.g., libraries, frameworks, or programming languages) with their version numbers. |
| Experiment Setup | Yes | We fixed n = 1000, d = 15000, λ = 0.01, and the convergence criteria was the relative duality gap (with threshold ϵ = 10 4). |