Enhanced microfluidic sensing platform for particle detection.
problem Electronically acquiring spatially separated particle information in lab-on-a-chip devices.
method Microfluidic CODES combining resistive pulse sensing and code division multiple access.
result Non-orthogonal code waveforms and machine learning for improved multiplexing.
Deep learning improves SCMA decoding and codebook construction for 5G wireless networks.
problem Designing low complexity high accuracy decoding algorithms and constructing optimal SCMA codebooks.
method Proposed a deep neural network (DNN) called DL-SCMA and an autoencoder (AE-SCMA) to learn and reconstruct SCMA modulated signals.
result Deep learning SCMA decoder outperforms conventional algorithms in BER, SER, and computational complexity.
Paper tackles division difficulty, proposing new methods to improve accuracy.
problem Division is the most challenging arithmetic operation for both humans and computers.
method Proposes two novel approaches: Neural Reciprocal Unit (NRU) and Neural Multiplicative Reciprocal Unit (NMRU), and improves an existing division module.
result Improves division accuracy from 70.2% to 91.6%.
Paper tackles structure learning of sparse GGMs over multiple access networks.
problem Estimating sparse Gaussian Graphical Model structure from multiple local machines with limited communication.
method Proposes Signs and Uncoded methods for reliable structure learning under power and bandwidth limitations.
result Both methods can recover the structure with high probability for large enough sample size.
HiPart offers an efficient, interactive tool for hierarchical clustering.
problem Efficient and interpretable hierarchical clustering for Big Data.
method Divisive hierarchical clustering algorithms with interactive visualizations.
result High computational efficiency and interpretability in Big Data applications.
Private method measures nonlinear correlations between data hosted across two entities.
problem Measuring nonlinear correlations between sensitive data hosted across multiple parties while preserving privacy.
method Differentially private estimator of distance correlation.
result First private estimator of nonlinear correlations in a multi-party setup.
Paper proposes neural network for LDPC coded DCO-OFDM with clipping distortion.
problem Mitigating nonlinear clipping distortion in LDPC coded DCO-OFDM systems.
method Designs a neural network-aided bit-interleaved coded modulation (NN-BICM) receiver to improve log-likelihood ratio (LLR) through backpropagation training.
result Neural network-aided receiver achieves noticeable performance gains over other methods.
The paper introduces InfoRL, a method to learn multiple ways to perform tasks in complex environments.
problem Learning a single best policy for tasks in complex environments.
method InfoMax approach to discover multiple latent codes for task performance.
result It is possible to learn multiple ways to perform tasks in complex environments using information maximization.
Paper introduces DACAL for high-resolution photo and video enhancement.
problem Photo and video enhancement with weak supervision.
method Divide-and-conquer adversarial learning approach with hierarchical decomposition.
result State-of-the-art performance in high-resolution photo and video enhancement.
Study explores efficient data division for ICPs.
problem Efficiently dividing limited development data for ICPs.
method Experiments with training, calibration, and test data divisions.
result Allows overlap between training and calibration sets improves efficiency.
The paper provides an algorithm to create curves touching a smooth cubic at specific intersection points.
problem Creating curves that touch a smooth cubic at specific intersection points.
method Algorithm based on divisions and Zariski tuples to produce n-contact curves. result An algorithm to generate n-contact curves to a smooth cubic. Paper models and compresses wideband CSI feedback in FDD MIMO systems.
problem Fundamental limits of channel state information (CSI) feedback in FDD massive MIMO systems.
method Modeling CSI as a Gaussian-mixture source with latent geometry states, proposing Gaussian-mixture transform coding (GMTC).
result Near-optimal CSI compression achieved through state-adaptive transform coding without large neural encoders.
This thesis is concerned with the residues modulo 4 and 8 of the signature of a 4k-dimensional oriented geometric Poincare complex. The Z_8-valued Brown-Kervaire invariant of Z_4-valued quadratic forms is used to prove that if the signature is divisible by 4, the divisibility by 8 is detected by the Arf invariant of a …
Deep RL for dynamic pricing of express lanes considers multiple origins, destinations, and access locations.
problem Dynamic pricing of express lanes with multiple access points and traveler heterogeneity.
method Formulated as a POMDP, uses policy gradient methods and neural networks to determine stochastic tolls.
result Deep RL outperforms traditional methods in maximizing revenue and minimizing travel time.
BiQGEMM efficiently multiplies quantized DNN weights using lookup tables.
problem Efficiently multiplying quantized DNN weights on CPUs/GPUs with limited memory.
method BiQGEMM pre-computes and stores redundant intermediate results in lookup tables.
result BiQGEMM achieves lower overall computations and higher performance.
New algorithms for fair item allocation with limited copies.
problem Fair division of numerous items with few copies.
method Modeling as a contextual bandit problem with sub-linear regret guarantees.
result Proposed algorithms achieve sub-linear regret in fair item allocation.
DeepCMC compresses CSI for massive MIMO systems, reducing overhead and improving performance.
problem High CSI overhead in massive MIMO systems limits spectral efficiency.
method Deep learning-based fully convolutional neural network with residual layers and entropy coding.
result DeepCMC outperforms state-of-the-art schemes in CSI reconstruction quality for the same compression rate.
This a free translation with additional explanations of {\em Processus à Accroissement Independants Chapitre I: La Décomposition de Paul Lévy}, by J.L. Bretagnolle, in {\em Ecole d'Eté de Probabilités}, Lecture Notes in Mathematics 307, Springer 1973. The Lévy-Khintchine representation of infinitely divisible distribut…
Proposes CNN-based analog CSI feedback for FDD MIMO-OFDM systems.
problem High CSI feedback overhead in FDD MIMO systems.
method AnalogDeepCMC: maps downlink CSI to uplink channel input, reconstructs channel estimate.
result Significantly improves downlink spectral efficiency and simplifies operation.
A new proof of an extension theorem with bounded generators.
problem Extension theorems in complex analysis.
method Skoda-type L2 division theorem with bounded generators. result The new division theorem allows α to be 1 in the norm of the datum. This paper explores how random sampling and coding can speed up approximate matrix multiplication.
problem Efficiently computing large-scale matrix multiplications in distributed systems.
method Proposes two schemes: coding for recovery and random sampling for approximation.
result Investigates tradeoffs between recovery threshold and approximation error.
Extends Optimal Transport to multiple agents, aiming for equitable and optimal distribution.
problem Sharing costs or goods equitably among multiple agents with different preferences.
method Minimizes the maximum transportation cost or maximizes the minimum utility.
result Provides a new algorithm faster than standard linear programming.
Study improves efficiency of MIMO systems' sum rate estimation.
problem Maximizing sum rate in MIMO systems with PAPC constraints.
method Proposes two new low-complexity approaches: alternating optimization and machine learning.
result Demonstrates superior performance compared to existing methods.
Solves division problem for L. Hörmander's systems.
problem Division problem for L. Hörmander's overdetermined systems.
method Formulates and proves divisibility criterion, coherence theorem.
result Establishes effective divisibility criterion and extends coherence theorem.
C-Learning estimates reachability over time to solve multi-goal tasks.
problem Multi-goal reaching challenges in reinforcement learning.
method Cumulative accessibility functions and recurrence relations.
result Optimal cumulative accessibility functions are monotonic in horizon.
Proves divisibility relations for symplectic curve polynomials.
problem Divisibility relations for symplectic curve polynomials.
method New proofs of divisibility relations for Oka and Alexander polynomials of symplectic curves.
result Proves Libgober's divisibility relations for symplectic curves.
Uniform convexity in divisible domains leads to hyperbolic geometry.
problem Understanding the geometry of divisible convex sets in Finsler manifolds.
method Proving β-uniform convexity of a specific Finsler metric. result A strictly convex divisible domain induces a β-uniformly convex Finsler metric. Tropical division approximates polynomial division for neural networks.
problem Approximating polynomial division in max-plus semiring.
method Approximating Newton Polytope of dividend by divisor, then applying to neural networks.
result Minimizes a two-layer fully connected network for binary classification.
Deep learning predicts downlink channel from uplink data, reducing signaling overhead.
problem Large signaling overhead for full DL CSI in FDD MIMO.
method Deep learning-based channel extrapolation (prediction).
result Deep learning can infer DL CSI from UL CSI without additional overhead.
Paper develops a decoder for sparse codes without encoder matrix, achieving optimal recovery.
problem Designing a decoder for sparse codes from linear measurements alone.
method Matrix factorization to recover encoder and sparse coding matrices from measurements.
result Decoder-Expander Based Factorisation recovers encoder and sparse coding matrix at optimal measurement rate with high probability.
A new method avoids noise amplification when subtracting or dividing stochastic signals.
problem Noise amplification when subtracting or dividing stochastic signals.
method Normalizing flows to approximate the distribution of the signal of interest.
result Normalizing flows can generate an approximation of the probability distribution over the signal of interest, avoiding subtraction or division.
In contrast to the many examples of convex divisible domains in real projective space, we prove that up to projective isomorphism there is only one convex divisible domain in the Grassmannian of p-planes in R2p when p>1. Moreover, this convex divisible domain is a model of the symmetric space associ…
Division algorithm for surface group rings yields standard complexes and cohomological dimensions.
problem Understanding cohomological dimensions of surface group actions.
method Division algorithm for group rings of surface groups.
result Some 2-complexes with surface fundamental groups are standard.
Adopting a zonal structure of electricity market requires specification of zones' borders. In this paper we use social welfare as the measure to assess quality of various zonal divisions. The social welfare is calculated by Market Coupling algorithm. The analyzed divisions are found by the usage of extended Locational …
Machine learning used in German official statistics.
problem Identifying areas and tasks where machine learning is applied in official statistics.
method Surveys conducted at statistical institutions and divisions of Destatis.
result Machine learning methods are used in various statistical areas and tasks.
Coded Federated Learning speeds up training in edge computing networks.
problem Slow convergence in Federated Learning due to heterogeneity and stochastic fluctuations.
method Exploiting statistical properties of compute and communication delays, distributed kernel embedding, and random Fourier features.
result Significant performance gains for CodedFedL in distributed non-linear regression and classification problems.
Paper uses machine learning to optimize UAV deployment for traffic offloading.
problem Optimizing UAV deployment for efficient traffic offloading from ground BSs.
method LSTM for traffic prediction, KEG algorithm for service area determination, multi-access techniques comparison.
result RSMA reduces up to 24% total power consumption compared to conventional methods.
Study provides long-term EMG data for multi-day biometric authentication.
problem Limited long-term EMG data for multi-day biometric authentication.
method Collected EMG data from 43 participants over three days.
result Multi-day biometric authentication results in low error rates.
A new method learns manifold-valued latents without an encoder.
problem Distorting data with intrinsic non-Euclidean structure.
method Riemannian generative decoder that learns latents directly.
result Learned representations respect the prescribed geometry and capture intrinsic non-Euclidean structure.
Geometrically explains divisibility of Euler classes for spin modules.
problem Divisibility of KO-theoretical Euler classes for spin modules. method Geometric interpretation of divisibility using spin structures and Seiberg-Witten theory.
result Clarifies the role of reducibles in monopole equations.
New proof of divisibility property for certain algebraic varieties.
problem Divisibility property for LQEL varieties.
method Construction of Clifford algebra representations to Severi varieties.
result New proof of Russo's Divisibility Property for LQEL varieties.
The paper sets lower bounds on envy-free divisions in cake-cutting problems.
problem Finding the minimum number of envy-free divisions in cake-cutting problems.
method Analyzes two scenarios: classical and hybrid, with different constraints and allocations.
result Sharp bounds and examples for envy-free divisions in both scenarios.
The paper revisits Rokhlin's divisibility theorem and its significance.
problem Rokhlin's divisibility theorem on signatures of manifolds.
method Overview and retrace of Rokhlin's proof and further developments.
result Reaffirms the importance of Rokhlin's theorem in manifold theory.
Proves Skoda's Division Theorem using degeneration and positivity of direct image bundles.
problem Division Theorem in Skoda's context
method Degeneration approach inspired by B. Berndtsson and L. Lempert's L2 extension theorem result Simplified and extended proof of L2 extension theorem Under certain integrability and geometric conditions, we prove division theorems for the exact sequences of holomorphic vector bundles and improve the results in the case of Koszul complex. By introducing a singular Hermitian structure on the trivial bundle, our results recover Skoda's division theorem for holomorphic …
A new hashing framework learns multiple hash codes for each image to improve hash bucket search efficiency.
problem Existing hashing methods fail to handle complex image retrieval scenarios efficiently.
method Multiple Code Hashing (MCH) framework with deep reinforcement learning.
result Significant improvement in hash bucket search performance compared to single-code methods.
The paper explains the topological origin of the distinction between incidence theorems over division rings and fields.
problem Understanding the distinction between incidence theorems over division rings and fields.
method Extending the surface-graph approach to noncommutative settings, the paper analyzes the topological properties of graphs embedded on surfaces of different genera.
result Theorems associated with graphs on the sphere hold over any division ring, while those on surfaces of positive genus typically hold only if the ground ring is a field.
Constructs projective plane over octonions, proving no higher real division algebras.
problem Existence of higher-dimensional real division algebras.
method Using Adams' solution of the Hopf invariant 1 problem, constructs projective plane over octonions.
result No higher-dimensional real division algebras exist.