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AI Rally Has 'Room To Go' Says Ozan Tarman
The artificial-intelligence trade locked in fresh gains on Monday, allowing global equities to shrug off a rebound in oil prices as the US and Iran remained deadlocked over a peace deal. Ozan Tarman, Global Macro Vice Chair at Deutsche Bank joined Stephen Carroll and Lizzy Burden to discuss the the moves in stocks as where Bond yields go from here.
KKR’s McVey Says Fed’s Warsh to ‘Do No Harm’ at June Meeting
KKR’s McVey Says Fed’s Warsh to ‘Do No Harm’ at June Meeting Henry McVey, balance sheet CIO and head of global asset and macro allocation at KKR, discusses his expectations for the upcoming Federal Reserve decision and offers insight into the firm’s midyear outlook.
Schonfeld Sees Possible Yield Spike If Burnham Wins
Colin Lancaster, EMEA Head and Global Co-Head of Discretionary Macro and Fixed Income at Schonfeld, discusses the gilt market and how the upcoming Makerfield by-election may deliver further volatility.
Inflation hits 3.2%, highest since 2023: Are ECB rate hikes inevitable?
Eurozone inflation rose to 3.2% in May, the highest since 2023, driven by energy and services. Markets now see an ECB rate hike next week as done deal. Price pressures across the euro area accelerated again in May, as the disruptions from the Strait of Hormuz blockade continued to ripple through energy markets, pushing inflation to its highest level in almost three years and cementing expectations of an imminent European Central Bank rate hike.
AdaGRPO: A Capability-Aware Adaptive Enhancement for Flow-based GRPO
Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) has demonstrated remarkable success in aligning text-to-image (T2I) flow models with human preferences. However, we have identified that the learning loop of current flow-based GRPO is fundamentally decoupled from the learner's current capability, suffering from critical blind spots at both prompt selection and advantage estimation: (i) Existing methods sample prompts randomly, overlooking the substantial impact of data...
Cohort-based Semantic Labeling: AI-Enabled Recovery of Visualization Semantics from Deployed SVGs
arXiv:2606.09782v1 Announce Type: new Abstract: Many web-based visualizations are deployed as Scalable Vector Graphics (SVG), a format that faithfully preserves visual appearance but typically omits the higher-level semantic structure needed for machine interpretation. Once rendered and published, information about a visualization's components, roles, and encodings is no longer explicitly available, limiting downstream operations such as querying, accessibility augmentation, explanation,...
German industrial output rises for the first time this year but is still 'too little'
An uptick of 0.4% in Germany's April factory output and a rise in exports offer little cause for celebration as new orders collapse, energy prices soar and Europe's largest economy continues to struggle to find solid footing. German industrial production edged higher in April for the first time since the outbreak of war in the Middle East, official data released Tuesday showed, though analysts warn the single-month gain masks a far grimmer underlying picture for Europe's largest economy....
EnclaveScale: Hardware-Assisted Edge-DP for Secure Data Centre Power Telemetry
arXiv:2606.09163v1 Announce Type: new Abstract: EnclaveScale is a distributed, hardware-assisted telemetry architecture providing post-extraction attestation, enabling operators to collaboratively model high-resolution generative AI power transients. Existing cryptographic techniques scale poorly for 10-Hz streaming or fail to authenticate origins, permitting malicious hosts to spoof sensor inputs. We implement and evaluate a post-extraction pipeline utilizing DCAP attestation, differential...
ORACLE-CT: Anatomy-Aware Support Pooling for CT Classification
Announce Type: new Abstract: Abdominal CT disease classification is challenging because each scan is a large 3D volume with many possible findings, while diagnostic evidence is often confined to specific organs or anatomical compartments. Most study-level classifiers aggregate encoder features using anatomy-agnostic pooling or attention, creating a mismatch between localized disease evidence and global evidence aggregation. We propose ORACLE--CT, an encoder-agnostic anatomy-aware aggregation...
Early Detection of Alzheimer's Disease Using Explainable Machine Learning on Clinical Biomarkers: A Multi-Class Classification Study Using the Alzheimer's Disease Neuroimaging Initiative (ADNI) Dataset
Announce Type: new Abstract: Background: Alzheimer's disease (AD) affects over 55 million people worldwide. Accurate, interpretable detection of normal cognition (NC), mild cognitive impairment (MCI), and AD from routine clinical assessments remains a critical unmet need. Methods: An XGBoost classifier was developed for three-class detection using eight clinical features from the Alzheimer's Disease Neuroimaging Initiative (ADNI): MMSE, CDR Global, CDR Sum of Boxes (CDR-SB), MoCA, FAQ, age,...