Posters

Freya PAGE achieves optimal time complexity for large-scale nonconvex finite-sum optimization using asynchronous and heterogeneous computations, overcoming limitations of prior methods.

FGTI: a novel frequency-aware model significantly improves multivariate time series imputation by focusing on the often-overlooked residual term, leveraging high-frequency information to enhance accur…

Frequency Adaptive Normalization (FAN) significantly boosts non-stationary time series forecasting accuracy by using Fourier transforms to identify and model dynamic trends and seasonal patterns, achi…

FreqMark: Robust invisible image watermarking via latent frequency space optimization, resisting regeneration attacks and achieving >90% bit accuracy with high image quality.

FreqBlender enhances DeepFake detection by cleverly blending frequency domain knowledge of real and fake faces, improving model generalization and providing a complementary strategy to existing spatia…

FreeSplat achieves state-of-the-art novel view synthesis by accurately localizing 3D Gaussians from long image sequences, overcoming limitations of prior methods confined to narrow-range interpolation…

FreeLong: Generate high-fidelity long videos without retraining using spectral blending of global and local video features!

FedEgoists: A novel FL collaboration formation strategy mitigating free-riders & conflicts in cross-silo business settings, ensuring optimal coalition formation for improved model performance.

Boost pathology model accuracy with Concept Anchor-guided Task-specific Feature Enhancement (CATE)! This adaptable paradigm enhances feature extraction for specific tasks using task-relevant concepts,…

LLMs’ success is explained by the self-similar, long-range dependent fractal structure of language; small-scale patterns reflect larger ones.

FeINFN: a novel Fourier-enhanced Implicit Neural Fusion Network, achieves state-of-the-art hyperspectral image fusion by innovatively combining spatial and frequency information in both the spatial an…

This work proposes FACL, a novel loss function for precipitation nowcasting, improving forecast sharpness and meteorological skill without sacrificing accuracy.

FouRA: a novel low-rank adaptation method improves text-to-image generation by learning projections in the Fourier domain and using an adaptive rank selection strategy, addressing LoRA’s limitations o…

First oracle-free, computationally tractable algorithms for provably convergent multivariate distributional RL are introduced, achieving convergence rates matching scalar settings and offering insight…

Zero-shot learning achieves accurate Markov jump process inference across diverse datasets, eliminating the need for extensive model retraining.

Ms-PoE, a simple plug-and-play positional encoding, significantly improves LLMs’ ability to utilize long contexts by mitigating the ’lost-in-the-middle’ problem and enhancing the capacity to capture i…

NsCE framework tackles key OCL challenges: model ignorance (learning effective features in limited time) and myopia (overly simplified features). NsCE integrates non-sparse maximum separation regulari…

FOOGD: A novel federated learning framework that simultaneously tackles out-of-distribution generalization and detection by estimating probability density for reliable global distribution guidance.

SMG (Separated Models for Generalization) enhances visual RL generalization by disentangling task-relevant and irrelevant visual features via cooperative reconstruction, achieving state-of-the-art per…

Fourier Neural Processes (FNP) revolutionizes data assimilation by enabling accurate analysis of observations with varying resolutions, improving weather forecasting and Earth system modeling.