papers

Publications (16)

cs.LG2026

Hyperbolic Aware Minimization: Implicit Bias for Sparsity

Tom Jacobs, Advait Gadhikar, Celia Rubio-Madrigal +1

Understanding the implicit bias of optimization algorithms is key to explaining and improving the generalization of deep models. The hyperbolic implicit bias induced by pointwise o…

astro-ph.SR2015

Kepler Eclipsing Binary Stars. VII. The Catalog of Eclipsing Binaries Found in the Entire Kepler Data-Set

Brian Kirk, Kyle Conroy, Andrej Prša +47

The primary Kepler Mission provided nearly continuous monitoring of ~200,000 objects with unprecedented photometric precision. We present the final catalog of eclipsing binary syst…

cs.LG2026

SparseOpt: Addressing Normalization-induced Gradient Skew in Sparse Training

Mohammed Adnan, Rohan Jain, Tom Jacobs +4

Dynamic Sparse Training (DST) methods train neural networks by maintaining sparsity while dynamically adapting the network topology. Despite the promise of reduced computation, DST…

cs.LG2025

Pay Attention to Small Weights

Chao Zhou, Tom Jacobs, Advait Gadhikar +1

Finetuning large pretrained neural networks is known to be resource-intensive, both in terms of memory and computational cost. To mitigate this, a common approach is to restrict tr…

cs.LG2025

The Graphon Limit Hypothesis: Understanding Neural Network Pruning via Infinite Width Analysis

Hoang Pham, The-Anh Ta, Tom Jacobs +2

Sparse neural networks promise efficiency, yet training them effectively remains a fundamental challenge. Despite advances in pruning methods that create sparse architectures, unde…

astro-ph.EP2022

Planetesimals Around Stars with TESS (PAST): II. An M Dwarf "Dipper" Star with a Long-Lived Disk in the TESS Continuous Viewing Zone

Eric Gaidos, Andrew W. Mann, Bárbara Rojas-Ayala +6

Studies of T Tauri disks inform planet formation theory; observations of variability due to occultation by circumstellar dust are a useful probe of unresolved, planet-forming inner…

cs.LG2026

Implicit Bias of Mirror Flow in Homogeneous Neural Networks: Sparse and Dense Feature Learning

Tom Jacobs, Guido Montufar

We study the max-margin solutions reached by mirror flow in deep neural networks with homogeneous activation functions. Extending classical results on gradient flow, we derive a no…

astro-ph.EP2023

Giant Outer Transiting Exoplanet Mass (GOT 'EM) Survey: III. Recovery and Confirmation of a Temperate, Mildly Eccentric, Single-Transit Jupiter Orbiting TOI-2010

Christopher R. Mann, Paul A. Dalba, David Lafrenière +48

Large-scale exoplanet surveys like the TESS mission are powerful tools for discovering large numbers of exoplanet candidates. Single-transit events are commonplace within the resul…

astro-ph.EP2014

Planet Hunters. VI: An Independent Characterization of KOI-351 and Several Long Period Planet Candidates from the Kepler Archival Data

Joseph R. Schmitt, Ji Wang, Debra A. Fischer +29

We report the discovery of 14 new transiting planet candidates in the Kepler field from the Planet Hunters citizen science program. None of these candidates overlapped with Kepler…

cs.LG2026

Never Saddle for Reparameterized Steepest Descent as Mirror Flow

Tom Jacobs, Chao Zhou, Rebekka Burkholz

How does the choice of optimization algorithm shape a model's ability to learn features? To address this question for steepest descent methods --including sign descent, which is cl…

cs.LG2025

Sign-In to the Lottery: Reparameterizing Sparse Training From Scratch

Advait Gadhikar, Tom Jacobs, Chao Zhou +1

The performance gap between training sparse neural networks from scratch (PaI) and dense-to-sparse training presents a major roadblock for efficient deep learning. According to the…

cs.LG2025

Mirror, Mirror of the Flow: How Does Regularization Shape Implicit Bias?

Tom Jacobs, Chao Zhou, Rebekka Burkholz

Implicit bias plays an important role in explaining how overparameterized models generalize well. Explicit regularization like weight decay is often employed in addition to prevent…

cs.LG2026

Implicit Bias of SGD in Multivariate ReLU Networks: Effective Width Collapse

Shuang Liang, Tom Jacobs, Guido Montúfar

We study the implicit bias of noisy stochastic gradient descent in training wide two-layer ReLU networks for multivariate regression. In a mean-field regime, the training dynamics…

cs.LG2025

Mask in the Mirror: Implicit Sparsification

Tom Jacobs, Rebekka Burkholz

Continuous sparsification strategies are among the most effective methods for reducing the inference costs and memory demands of large-scale neural networks. A key factor in their…

astro-ph.EP2023

Kepler's Last Planet Discoveries: Two New Planets and One Single-Transit Candidate from K2 Campaign 19

Elyse Incha, Andrew Vanderburg, Tom Jacobs +9

The Kepler space telescope was responsible for the discovery of over 2,700 confirmed exoplanets, more than half of the total number of exoplanets known today. These discoveries too…

cs.LG2026

HORST: Composing Optimizer Geometries for Sparse Transformer Training

Tom Jacobs, Rohan Jain, Rebekka Burkholz

Sparsifying transformers remains a fundamental challenge, as standard optimizers fail to simultaneously encourage sparsity and maintain training stability. Effective adaptive optim…