A specific class of subsets of R^3 containing all algebraic sets admits minimum adapted CADs, giving the first positive existence theorem for such decompositions in dimension three.
C., Hinneburg, A., & Keim, D
9 Pith papers cite this work. Polarity classification is still indexing.
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Boundary mass in MoE is linear in slab width under smoothness and transversality, so the zero-temperature limit is governed by a thin geometric layer around routing interfaces rather than the full input space.
Small 7B reasoning models were fine-tuned on synthetic and curated QFT problems using RL and SFT, yielding performance gains, error analysis, and public release of data and traces.
Empirical integral operators with discontinuous non-negative symmetric kernels converge spectrally to their population versions with explicit rates as sample size grows to infinity.
k-contact geometry supplies explicit Hamiltonian descriptions for multiple dissipative PDEs including damped Klein-Gordon, Allen-Cahn, Fisher-KPP, and complex Ginzburg-Landau equations.
Bulk-edge correspondence for fractional quantum Hall systems is realized as relative higher gauge theory from the complex Hopf fibration, geometrically engineered via M2/M5-branes and TED Cohomotopy flux quantization.
WARM-VR provides a new public dataset of wristband and ECG signals from 31 people in VR stress-relaxation experiences with olfactory cues, plus baseline ML classification results for valence and arousal.
A template-based lemma generation method integrated into bounded rewriting induction for higher-order LCSTRSs enables proving program equivalences previously out of reach.
Simulations show Ridge, Lasso, and ElasticNet perform similarly for prediction at high sample-to-feature ratios, but Lasso feature selection recall drops to 0.18 under high multicollinearity and low SNR while ElasticNet holds at 0.93.
citing papers explorer
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On Minimum CADs for Algebraic Sets in Dimension Three
A specific class of subsets of R^3 containing all algebraic sets admits minimum adapted CADs, giving the first positive existence theorem for such decompositions in dimension three.
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Boundary Mass and the Soft-to-Hard Limit in Mixture-of-Experts
Boundary mass in MoE is linear in slab width under smoothness and transversality, so the zero-temperature limit is governed by a thin geometric layer around routing interfaces rather than the full input space.
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Fine-Tuning Small Reasoning Models for Quantum Field Theory
Small 7B reasoning models were fine-tuned on synthetic and curated QFT problems using RL and SFT, yielding performance gains, error analysis, and public release of data and traces.
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Spectral convergence of empirical integral operators with discontinuous kernels
Empirical integral operators with discontinuous non-negative symmetric kernels converge spectrally to their population versions with explicit rates as sample size grows to infinity.
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A Guide to Applications of $k$-Contact Geometry in Dissipative Field Equations
k-contact geometry supplies explicit Hamiltonian descriptions for multiple dissipative PDEs including damped Klein-Gordon, Allen-Cahn, Fisher-KPP, and complex Ginzburg-Landau equations.
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Bulk-Edge Correspondence via Higher Gauge Theory
Bulk-edge correspondence for fractional quantum Hall systems is realized as relative higher gauge theory from the complex Hopf fibration, geometrically engineered via M2/M5-branes and TED Cohomotopy flux quantization.
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Introducing WARM-VR: Benchmark Dataset for Multimodal Wearable Affect Recognition in Virtual Reality
WARM-VR provides a new public dataset of wristband and ECG signals from 31 people in VR stress-relaxation experiences with olfactory cues, plus baseline ML classification results for valence and arousal.
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Templates in Rewriting Induction
A template-based lemma generation method integrated into bounded rewriting induction for higher-order LCSTRSs enables proving program equivalences previously out of reach.
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Choosing the Right Regularizer for Applied ML: Simulation Benchmarks of Popular Scikit-learn Regularization Frameworks
Simulations show Ridge, Lasso, and ElasticNet perform similarly for prediction at high sample-to-feature ratios, but Lasso feature selection recall drops to 0.18 under high multicollinearity and low SNR while ElasticNet holds at 0.93.