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Full Bengal cabinet today: BJP balances old-versus-new, regional aspirations
Kolkata : The need to strike a balance among Bengal’s various regions and between BJP veterans and new entrants was among the factors that weighed heavily on the party leadership during the selection of ministers who will be sworn in on Monday. Chief minister Suvendu Adhikari wrote on his X handle on Sunday that 35 ministers will take oath in the first expansion of the council of ministers since Bengal’s first BJP govt took up office on May 9. The govt is now functioning with six ministers,...
Shopping for America 250? Here's what's actually made in the USA — and what's imported
As America 250 approaches, more shoppers are seeking out products made in the United States. We rounded up standout American-made brands and identified which products are still manufactured domestically and which ones are imported. From All American Clothing jeans and Estwing tools to select New Balance sneakers and All-Clad cookware, these are the tried-and-true American-made picks worth buying.
SIGMA: A Versatile Streaming Graph Partitioner for Vertex- and Edge-Balanced Distributed GNN Training
Announce Type: new Abstract: Distributed Graph Neural Network (GNN) training depends critically on how the underlying graph is partitioned across compute resources. Existing graph partitioners focus either on vertex partitioning or edge partitioning and typically optimize only a single communication objective (edge cut or vertex cut) under a single balance constraint (vertex balance or edge balance).
Continual Learning as a Multiphase Moving-Boundary Problem
arXiv:2606.01863v1 Announce Type: new Abstract: Continual learning struggles to balance retaining past knowledge with absorbing new tasks. Stefan-CL elegantly resolves this stability-plasticity dilemma through the physics of melting. It frames consolidated knowledge as a protected "solid" and unused capacity as an adaptable "liquid."
Hybrid Imbalanced Regression Through Unified Data-Level and Algorithm-Level Balancing
Announce Type: new Abstract: Imbalanced learning is a critical challenge in machine learning, where underrepresented target values can bias models and degrade prediction performance on rare but important cases. Although extensively studied in classification, imbalanced regression remains relatively underexplored. Existing methods mainly focus on either data-level balancing, which may introduce noise and overfitting, or algorithm-level balancing, which often struggles with highly complex...
Complexity-Balanced Diffusion Splitting
new Abstract: Standard continuous-time generative models rely on monolithic architectures that must navigate vastly different signal regimes, from isotropic noise to intricate data distributions. While scaling model capacity improves performance, deploying a massive network uniformly across the entire generative timeline is inherently inefficient. In this work, we propose Complexity-Balanced Splitting (CBS), a principled framework for temporal capacity allocation that distributes the...
Revisiting Prototype Rehearsal for Exemplar-Free Continual Learning: Manifold-Aware Boundary Sampling with Adaptive Class-Balanced Loss
Announce Type: new Abstract: Exemplar-free class-incremental learning (EFCIL) aims to acquire new classes over time without storing raw data. Historically, prototype rehearsal, which samples around stored class prototypes and mixes them with current-task data, has been a popular strategy to reduce catastrophic forgetting. However, recent drift-compensation methods that explicitly realign prototypes in the evolving feature space consistently outperform prototype-based rehearsal, raising the...
Save up to 50% on top-rated sneakers before Prime Day — from Skechers to adidas
You don't have to wait until Prime Day kicks off to upgrade your sneaker collection for less. With these early deals on brands like Skechers, New Balance and Dr. Scholl's, you can save up to 50% on best-selling pairs weeks before the rush. We've found options for both men and women with discounted styles for walking, working and everyday wear.
Next-Generation Parallel Decoder for LPDR: Architectural Optimization and Class-Balanced GAN-Augmentation
Announce Type: new Abstract: Real-Time License Plate Detection and Recognition (LPDR) forms the backbone of modern smart cities. Although the YOLOV5-PDLPR model substantially improved system efficiency through a parallel decoder approach, its performance is still affected by spatial character mismatches and data imbalance within the training set. This paper addresses these limitations by introducing Cross-Spatial Hybrid Attention (CSHA) and Class-Balanced Synthetic Augmentation (CBSA).
UltraEP: Unleash MoE Training and Inference on Rack-Scale Nodes with Near-Optimal Load Balancing
arXiv:2606.04101v1 Announce Type: new Abstract: Large-scale expert parallelism (EP) is becoming pivotal for training and serving frontier MoE models, but it also amplifies device-level expert load imbalance into compute stragglers, token all-to-all bottlenecks, and activation-memory spikes. Existing balancers redistribute experts periodically based on historical load, which becomes unreliable for production deployments with non-stationary load patterns. We present UltraEP, the first...