121 problems
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Heavy-tailed target conjecture for outlier and power-law weight spectra
Consider a model whose target spectral distribution is heavy-tailed, in contrast with the Marchenko–Pastur target distribution discussed above. Heavy-tailed target conjecture. A mo…
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Lacasse's conjecture on the PAC-Bayesian combinatorial sum
Lacasse's conjecture. For every ,
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High-accuracy conjecture for rational Gröbner basis computation beyond the input-length constraint
High-accuracy conjecture. High accuracy should still be achievable over the field of rational numbers when
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Wasserstein distance superiority conjecture for MNIST classification
Wasserstein distance superiority conjecture. For a very large training set, the Wasserstein distance will have better performance than each of the three tested distances.
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The capability convergence hypothesis for machine intelligence
The paper studies machine intelligence as a system whose capabilities may depend not only on representational structure but also on access structure. Capability convergence hypothe…
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The proposed functional form for collinearity as a function of correlation and dimension
Let denote the collinearity parameter, the correlation parameter, and the number of variables in the latent linear-regression framework described above. Proposed f…
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Class-switching conjecture for prevalence-weighted cross-entropy
Let be a binary softmax function with elements and that minimize the prevalence-weighted cross-entropy objective in the infinite-sample limit, where…
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Poseidon's prior-knowledge conjecture for fluid-type PDE datasets
The [? Let Poseidon be a neural operator model pretrained on fluid-type datasets, and consider the INS-Tracer equation dataset, whose physical mechanisms include incompressible Nav…
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Conjecture that stochastic optimization reduces EFS computational cost
EFS has a forward optimization step whose time complexity is quadratic in the number of training samples. Stochastic optimization conjecture. Stochastic optimization techniques cou…
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Conjecture on the cause of poor one-step CCA+LoRA prediction
CCA+LoRA one-step conjecture. The particularly poor prediction quality of CCA+LoRA when is caused by the absence of the action of Koopman matrices.
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Benning et al.'s conjecture on non-stationary isotropic covariance kernels in machine learning
Let a Gaussian process be used to model an error, cost, or risk function in machine learning, and consider covariance kernels that are isotropic but non-stationary. Benning et al.'…
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Improved sample-complexity upper bound for the gap-closed score
A cutting-plane learning problem considers candidate cuts evaluated by a gap-closed score, with attention restricted to cuts that cut off the current fractional solution. Gap-close…
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Strong ironing property for rolling-ball optimizers
Let be two continuous functions, and let be their respective graphs. Write…
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The modulus determination conjecture for Dirichlet characters
Let be an integer, let be a Dirichlet character modulo , and let … be its Dirichlet -function. Denote its initial non-trivial z…
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The generic statistical-ensemble conjecture for Attention schemes
Generic statistical-ensemble conjecture. All Attention schemes are variants of a generic, abstract statistical ensemble, with a more complete set of pairwise and/or higher-order in…
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The CNN locality conjecture for out-of-distribution inverse scattering
Consider convolutional neural networks used in inverse-scattering reconstruction, with convolution blocks providing local operations, and consider scatterers outside the training d…
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The scalability conjecture for aligned multi-objective optimization
Aligned multi-objective optimization (AMOO) considers multiple related loss functions whose feedback is aligned or approximately aligned during optimization. In this setting, algor…
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Conjecture on tuning bias from the number of tuned parameters in conformal prediction
Tuning-parameter conjecture. The observed differences in tuning bias may be due to the large number of parameters tuned in these methods.
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The conjecture that LSUN Kitchen has more complex underlying topology than CelebA
Topological complexity conjecture. Since LSUN Kitchen is a much larger dataset containing diverse images, its underlying lower-dimensional submanifold has more complex topological…
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The randomized-graph suitability conjecture for CGL
Let CGL denote the paper’s coincidence-graph learning approach, applied to larger and more randomized graphs, and let the system’s recursive range measure how far graph interaction…
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The rest-state de-inforcement conjecture for computational agents
Consider an agent whose internal graph uses de-inforcement and which can enter a “rest” state with limited or no external stimuli. Rest-state de-inforcement conjecture. During such…
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The de-inforcement conjecture for dynamic graph representations
The model uses de-inforcement, meaning that plasticity reduces rather than amplifies signals in its internal graph representation. De-inforcement conjecture. The de-inforcement fun…
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The in-training flow group-properties convergence conjecture
A flow is a family of maps with group properties, and neural conjugate flows represent dynamics by composing an invertible map, a flow, and its inverse. Training may either impose…
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Sorting-order characterization conjecture for Stanley coefficients
For a partition , let be the set of -Escher tuples, let be the c…
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Sorting-order conjecture for Stanley coefficients of Escher tuples
For a partition , let be the set of -Escher tuples associated with , let…